text:
\section{Introduction}
\label{sec:intro}

In recent years, deep neural network (DNN) based automatic speech recognition (ASR) systems have been improved dramatically, which are, however, data-hungry.
A well-trained DNN based ASR system for a single language usually requires hundreds to thousands of hours of transcribed speech data.
Remarkably, there are more than 7100 languages in the world \cite{lewis}, and most of them are low-resourced languages, for which only limited transcribed speech data are available \cite{GlobalPhone}.

To advance ASR for low-resourced languages, multilingual and crosslingual speech recognition methods have long been developed, mainly for acoustic modeling \cite{Schultz98,Heigold,10.1109/TASLP.2015.2422573,tandem_is2010,Hermann_2018,idiap_arxiv17,Idiap_IS18} (More discussions in Section \ref{sec:related}).
Some end-to-end ASR models \cite{asru17,g_ic18,g_ic19} fold the acoustic model (AM), pronunciation lexicon and language model (LM) into a single neural network, making the models being even more data-hungry and not suitable for low-resourced multilingual speech recognition, which is the main problem we hope to solve in this work\footnote{We suppose that text corpus and pronunciation lexicons or grapheme-to-phoneme (G2P) transducers \cite{Mark_slsp20,novak-etal-2012-wfst} are available.}.

Intuitively, the key to successful multilingual and crosslingual recognition is to promote the information sharing in multilingual training and maximize the knowledge transferring from the well trained multilingual model to the model for recognizing the utterances in the new language.
To this end,  a common practice is that similar sounds across languages are combined into one multilingual phone set.
International Phonetic Alphabet (IPA), which classifies sounds based on phonetic knowledge, has been used to create a universal phone set \cite{Schultz98,idiap_arxiv17,2020That}.
Often phones are seen as being the ``atoms'' of speech. But it is now widely accepted in phonology that phones are decomposable into smaller, more fundamental units, sharable across all languages, called phonological distinctive features \cite{nla.cat-vn542882,King_csl00}.
Namely, phones can be represented by a set of phonological features, such as voicing, high, low (representing tongue position during vowels), round (for lip rounding), continuant (to distinguish sounds such as vowels and fricatives from stops) and so on, as shown in Table \ref{tab:PFfeature}.
As shown in Fig. \ref{fig:connect},  the use of phonological features potentially allow language-specific phones to remain linked — to ``share statistical strength'' in training. This is highly desirable, especially for zero-shot crosslingual speech recognition.

\begin{figure}[t]
\centering
\centerline{\includegraphics[width=6.5cm]{fig1}}
\vspace{-3mm}
\caption{Illustration of the connection between Spanish and Italian. As indicated by the intersection of the two circles, there are some common IPA phones used in both languages, which can be trained with more data from both languages.
Notably, there also exist language-specific phones for each language. \eth~and~\textepsilon~only appears in Spanish and Italian respectively, and thus are not linked in the surface forms.
The bottom show the phonological features for~\eth~and~\textepsilon, which share many common components. Phonological feature components are ordered as listed in Table \ref{tab:PFfeature}.}
\label{fig:connect}
\vspace{-4mm}
\end{figure}

\begin{figure}[t]
\centering
\centerline{\includegraphics[width=8cm]{methods}}
\vspace{-3mm}
\caption{(a) Phonology driven phone embedding (top-down) and DNN based acoustic feature extraction (bottom-up) are joined to calculate the logits, which define the phone probabilities.
(b) Traditional methods in using phonological features are purely bottom-up.}
\label{fig:methods}
\vspace{-3mm}
\end{figure}

Phonological features (PFs) have been applied in multilingual and crosslingual speech recognition \cite{cmu_EU03,Idiap_IS18}.
Previous studies generally take a bottom-up approach and train a phonological feature extractor, often implemented by neural networks.
Each training sample consists of a speech frame as the input and the canonical phonological feature components derived from the labeled phone as the target output values.
Multiple neural networks are trained, depending on the partition of the phonological features.
In the feature concatenation approach, the log posteriors of every phonological class are concatenated together and fed into the high-level acoustic model, which further predicts the phone probabilities \cite{Idiap_IS18}.
Alternatively, in the model combination approach, the PF probabilities and the phone probabilities from a standard acoustic model are combined to calculate the acoustic score \cite{cmu_EU03}.

A drawback suffered by previous methods in using phonological features is that the acoustic-to-PF extraction in a bottom-up way is itself difficult, let alone the training of the phonological feature extractor needs segmented and labeled speech at the phone level.
Moreover, previous methods do not provide a principled model to calculate the phone probabilities for unseen phones from the new language towards zero-shot crosslingual recognition.
The parameters connecting to the unseen phones in the output layer of the DNN model are initialized either randomly \cite{Schultz98} or in an ad-hoc way (taking a weighted average of the parameters of all the seen phones \cite{Idiap_IS18}).

In this paper, we propose a new approach to using phonological features for multilingual and crosslingual speech recognition.
As illustrated in Fig. \ref{fig:methods}(a), our approach consists of phonology driven phone embedding (top-down) and DNN based acoustic feature extraction (bottom-up), which are joined to calculate the logits to define the phone probabilities. This is different from the pure bottom-up manner of the traditional methods in using phonological features, as sketched in Fig. \ref{fig:methods}(b).

Specifically, by using binary encoding of phonological features, we first obtain an encoding vector for each phone in the IPA table, which is referred to as the \emph{phonological-vector}. Then, we apply linear or nonlinear transformation of the phonological-vector to obtain the phone embedding vector for each phone. This step is referred to as the phonological transformation (top-down). Next, we conduct bottom-up calculation on an acoustic DNN, viewed as a cascade of acoustic feature extractors.
Finally, the extracted acoustic features and the phone embeddings are joined to calculate the phone (posterior) probabilities, which can be further used to calculate the CTC loss \cite{Graves_CTC} or the CTC-CRF loss \cite{CTC-CRF-icssp2019,an2020cat}. This completes the definition of a multilingual acoustic model, which involves the Joining of Acoustics and Phonology and is thus called the JoinAP method.
Remarkably, no inversion from acoustics to phonological features is required for speech recognition.
Details about applying the JoinAP model to multilingual and crosslingual speech recognition are given in Section \ref{sec:method}.

To evaluate the JoinAP model, a series of multilingual and crosslingual (both zero-shot and few-shot) speech recognition experiments are conducted on the CommonVoice dataset (involving German, French, Spanish and Italian) \cite{ardila2020common} and the AISHLL-1 dataset (Mandarin) \cite{bu2017aishell1}. The main findings are as follows.
\begin{itemize}
    \item With JoinAP, we can develop a single acoustic model for multilingual speech recognition, which performs better than the traditional multilingual model (namely using flat phone embeddings\footnote{In the traditional multilingual model such as based on CTC or CTC-CRF, the weights of the final linear layer before softmax can be regarded as flat, unstructured phone embeddings. In contrast, JoinAP uses phonological-vector based, structured phone embeddings.}).
    \item In zero-shot crosslingual recognition, JoinAP with nonlinear phone embeddings outperforms both JoinAP with linear phone embeddings and the traditional model with flat phone embeddings significantly and consistently.
    \item In few-shot crosslingual recognition, using JoinAP with nonlinear phone embeddings still yields much better results than using flat phone embeddings; however, the superiority of nonlinear over linear for phone embeddings seems to be weakened, as there are more training data from the target languages.
\end{itemize}

\section{Related Work}
\label{sec:related}

In \emph{multilingual speech recognition}, training data for a number of languages, often referred to as seen languages, are merged to train a multilingual AM.
Multilingual training is found to outperform monolingual training, which trains the monolingual AMs separately for each seen language \cite{Heigold}. Such advantage is presumably due to the information sharing between seen languages in multilingual training.
A common approach is to share the lower layers of the DNNs between languages, while the output layers are language specific \cite{Heigold,10.1109/TASLP.2015.2422573}.
Another widely used approach is to extract the bottleneck features from the bottleneck layer of a multilingual DNN model, which are then used as input features to train the AM for the target language \cite{tandem_is2010,Hermann_2018}.

\emph{Crosslingual speech recognition} refers to recognizing utterances in a new language, which is unseen in training the multilingual AM.
In the zero-shot setting, the multilingual AM is trained and directly used without any transcribed speech from the new, target language \cite{Schultz98,2020That,2020How,LXJ_AAAI2020}.
Alternatively, in the few-shot setting, the multilingual AM can be further finetuned or adapted on limited transcribed speech from the new language \cite{idiap_arxiv17,Idiap_IS18,li2020universal}.
Hopefully, knowledge can be transferred, by adapting a well-trained multilingual model to the new language, presumably because the multilingual model should learn some universal phonetic representations and the new language is similar to seen languages, more or less.

Earlier studies in multilingual and crosslingual recognition use context-dependent phone units, which leads to an explosion of units and also needs special care to handle context-dependent modeling across languages \cite{eu01-triphone,Idiap_Ic19_LFMMI}.
There are recent attempts to use end-to-end ASR models such as CTC with monophones \cite{idiap_arxiv17,LXJ_AAAI2020} or end-to-end LF-MMI with biphones \cite{E2E-LF-MMI,Idiap_Ic19_LFMMI} for multilingual and crosslingual recognition.
Remarkably, the end-to-end CTC-CRF model, which is defined by a CRF (conditional random field) with CTC topology, has been shown to perform significantly better than CTC \cite{CTC-CRF-icssp2019,an2020cat}. Moreover, mono-phone CTC-CRF performs comparably to bi-phone end-to-end LF-MMI \cite{E2E-LF-MMI} and avoids context-dependent modeling with a simpler pipeline, which is particularly attractive for multilingual and crosslingual speech recognition.

When the phonological transformation is linear, our JoinAP model reduces to the model introduced in \cite{LXJ_AAAI2020}. But in \cite{LXJ_AAAI2020}, only zero-shot crosslingual phone recognition is conducted and the model is developed still in a bottom-up way without the idea of joining acoustics (bottom-up) and phonology (top-down).

\section{Method}
\label{sec:method}

This section first explains the definition and construction of phonological vectors. Then we describe the JoinAP method with linear and nonlinear phone embeddings. Finally, we introduce the CTC-CRF based ASR framework to use JoinAP.

\subsection{Phonological-vector}
\label{ssec:phononlogical}

Phonological (distinctive) features have been proposed as the basis of spoken language universals, in the sense that while the phones of a language vary, the set of phonological features does not and is the same for all languages.
That is, phones can be constructed from a set of phonological features.
As shown in Fig. \ref{fig:connect},  the use of phonological features potentially allow language-specific phones to remain linked, which could benefit the information sharing in multilingual training.

There are different phonological feature sets and phonological systems, among which one of the most popular systems is proposed by Chomsky and Halle in 1968~\cite{nla.cat-vn542882}.
Phonological features are categorized into four classes: major class features, manner of articulation features, source features, cavity features. Each feature is marked as `+', `-' or `0'. `+' indicates the presence of that feature, `-' indicates the absence, and `0' means certain phone does not show such feature; for example, it is meaningless for a vowel to possess consonant features, so it will be marked as `0'. In our experiment, we employ PanPhon \cite{mortensen-etal-2016-panphon} to obtain the phonological features for IPA symbols. PanPhon uses a total of 24 phonological features. Table \ref{tab:PFfeature} gives examples of the feature specifications of some IPA phones, where all 24 features are listed.

\begin{table}[t]
\centering
\caption{Phonological features of some IPA phones}
\label{tab:PFfeature}
\begin{tabular}{l|lllllll}
\hline
Phonological feature           & d  & \textepsilon & \eth & \textschwa & i &  \textdctzlig & k\textsuperscript{j}\\
\hline
syllabic          & -  & + & - & + & + &- &-\\
sonorant          & -  & + & - & + & + & -&-\\
consonantal       & +  & - & + & - & - & +&+\\
continuant        & -  & + & + & + & + & -&-\\
delayed release   & -  & - & - & - & - & +&-\\
lateral           & -  & - & - & - & - & -&-\\
nasal             & -  & - & - & - & - & -&-\\
strident          & 0  & 0 & 0 & 0 & 0 & 0&0\\
voice             & +  & + & + & + & + & +&-\\
spread glottis    & -  & - & - & - & - & -&-\\
constricted glottis & -  & - & - & - & - & -&-\\
anterior          & +  & 0 & + & 0 & 0 & -&-\\
coronal           & +  & - & + & - & - & +&-\\
distributed labial & -  & 0 & + & 0 & 0 & +&0\\
labial            & -  & - & - & - & - & -&-\\
high              & -  & - & - & - & + & +&+\\
low               & -  & - & - & - & - & -&-\\
back              & -  & - & - & + & - & -&-\\
round             & -  & - & - & - & - & -&-\\
velaric        & -  & - & - & - & - & -&-\\
tense             & 0  & - & 0 & - & + & 0&0\\
long             & -  & - & - & - & - & -&-\\
hitone             & 0  & 0 & 0 & 0 & 0 &0 &0\\
hireg             & 0  & 0 & 0 & 0 & 0 & 0&0\\
\hline
\end{tabular}
\vspace{-3mm}
\end{table}

Now each phone is described by 24 phonological features, and each feature can take `+', `-' or `0'. Further, we encode each phonological feature by a 2-bit binary vector.
Taking the feature ``round'' as an example, the first bit indicates whether it is ``round+'' and the second bit indicates ``round-''. Therefore, if the ``round'' feature takes `+', the 2-bit vector will be ``10''; if the ``round'' feature is `-', the 2-bit vector will be ``01''; if the ``round'' feature takes `0', the 2-bit vector will be ``00''.
In this way, we can represent the phonological features by a 48-bit vector. Additionally, acoustic training (e.g., based on CTC-CRF) introduces 3 special extra tokens (\verb|<blk>|, \verb|<spn>| and \verb|<nsn>|), so we further add another 3 bits to encode the three special tokens in one-hot.
In summary, we obtain a 51-bit encoding vector for each phone in the IPA table, which is referred to as the \emph{phonological-vector}.

\subsection{Phone embedding}

Based on the phonological-vector representation of phones, we propose to join phonology driven phone embedding (top-down) and DNN based acoustic feature extraction (bottom-up) to calculate the logits, which further define the phone probabilities for ASR.
This method, called JoinAP (Joining of Acoustics and Phonology), is different from the traditional bottom-up way to use phonological features for ASR (e.g., by building the phonological feature extactor) (See Fig. \ref{fig:methods} for illustration).

In the traditional multilingual model such as based on CTC or CTC-CRF, one may view the acoustic DNN as a cascade of bottom-up feature extractors.
At frame $t$, the DNN output $h_t \in \mathbb{R}^{H}$ could be viewed as the projection of speech into some abstract space, pertaining to the spoken phones.
Before softmax computation to output phone probabilities, the final linear layer calculates the logits as follows:
\begin{equation}
    \label{eq:linear}
    z_{t,i} = e_i^T h_t
\end{equation}
where $e_i \in \mathbb{R}^{H} $ denotes the weight vector in the final linear layer and could be viewed as a (flat) phone embedding vector for phone $i$.
For simplicity, we omit the bias in describing linear layers throughout the paper.

In JoinAP, we propose to apply linear or nonlinear transformation of the phonological-vector to obtain the phone embedding vector for each phone. This step is referred to as the phonological transformation (top-down) and explained as follows.

\paragraph*{The JoinAP-Linear method.} Given the phonological-vector $p_i \in \mathbb{R}^{51}$ for phone $i$, we apply linear transformation of $p_i$ to define the embedding vector for phone $i$:
\begin{equation}
    \label{eq:embedding}
    e_i=A p_i \in \mathbb{R}^{H}

\end{equation}
where $A \in \mathbb{R}^{H\times51}$ denotes the transformation matrix. The logits for calculating the phone (posterior) probabilities are still defined as in Eq. (\ref{eq:linear}), which can be transparently used in the CTC-CRF based ASR framework (detailed later).

\paragraph*{The JoinAP-Nonlinear method.} The nonlinear method is similar to the linear one, except that we apply nonlinear transformation of $p_i$ to define the embedding vector for phone $i$. In theory, multilayered neural networks could be used for phonological transformation. Here we consider to add one hidden layer as follows:
\begin{equation} \label{eq:nonlinear}

    e_i = A_2 \sigma(A_1 p_i) \in \mathbb{R}^H
\end{equation}
where $A_1, A_2$ denote the matrices of appropriate sizes, and $\sigma(\cdot)$ denote some nonlinear activation function (e.g. sigmoid).
The logits for calculating the phone (posterior) probabilities are still defined as in Eq. (\ref{eq:linear}).

\subsection{CTC-CRF based ASR}
In this section, we briefly explain the CTC-CRF based framework \cite{CTC-CRF-icssp2019, an2020cat} to use phone embeddings for ASR. Consider discriminative training with the objective to maximize the conditional likelihood~\cite{CTC-CRF-icssp2019}:
\begin{equation}
    \label{eq:crf-obj1}
    \mathcal{L}(\theta) = - \log p_{\theta}(\bm{l}|\bm{x})
\end{equation}
where $\bm{x} \triangleq (x_1, \cdots, x_T)$ is the speech feature sequence, $\bm{l} \triangleq (l_1, \cdots, l_L)$ is the phone-label sequence, and $\theta$ denotes the model parameters. Note that in speech recognition, $\bm{x}$ and $\bm{l}$ are in different lengths and not aligned. To handle this, a hidden state sequence $\bm{\pi} \triangleq (\pi_1,\cdots,\pi_T)$ and a map $\mathcal{B}(\cdot)$ for mapping $\bm{\pi}$ to $\bm{l}$ are introduced. The mapping function $\mathcal{B}$ removes consecutive repetitive labels and blanks in $\bm{\pi}$ to give $\bm{l}$. So the posterior of $\bm{l}$ is defined as:
\begin{equation}
    \label{eq:post-l}
	p_{\theta}(\bm{l} | \bm{x}) = \sum_{\bm{\pi} \in \mathcal{B}^{-1}(\bm{l})} p_{\theta}(\bm{\pi} | \bm{x})
\end{equation}
And the posterior of $\bm{\pi}$ is further defined by a conditional random field (CRF):
\begin{equation}
    \label{eq:post-pi}
    p_{\theta}(\bm{\pi}|\bm{x}) =
    \frac{\exp(\phi_{\theta}(\bm{\pi}, \bm{x}))}
    {\sum_{\bm{\pi}'}{\exp(\phi_{\theta}({\bm{\pi}', \bm{x}}))}}
\end{equation}
where $\phi_{\theta}(\bm{\pi}, \bm{x})$ denotes the potential function of the CRF, defined as:
\begin{equation} \label{eq:potential}
    \phi_{\theta}(\bm{\pi}, \bm{x}) = \log p(\bm{l})+ \sum_{t=1}^{T} \log p_{\theta}(\pi_t|\bm{x})
\end{equation}
where $\bm{l} = \mathcal{B}(\bm{\pi})$, and $p(\bm{l})$ is realized by an n-gram LM of labels. If $\log p(\bm{l})$ is omitted in Eq. (\ref{eq:potential}), the potential function becomes self-normalized and CTC-CRF reduces to regular CTC.
$p_{\theta}(\pi_t|\bm{x})$ represents the phone (posterior) probabilities, which are calculated by softmax from the logits $z_{t,i}$ in Eq. (\ref{eq:linear}) as follows:
\begin{displaymath}
p_{\theta}(\pi_t = i|\bm{x}) = \frac{\exp(z_{t,i})}{\sum_j \exp(z_{t,j})}
\end{displaymath}

Remarkably, regular CTC suffers from the conditional independence between the states in $\bm{\pi}$. In contrast, by incorporating $\log p(\bm{l})$ into the potential function in CTC-CRF, this drawback is naturally avoided.
It has been shown that CTC-CRF outperforms regular CTC consistently on a wide range of benchmarks, and is on par with other state-of-the-art end-to-end models~\cite{CTC-CRF-icssp2019, an2020cat, CTC-CRF-NAS}. Moreover, CTC-CRF enjoys data-efficiency in training and works well with mono-phones \cite{an2020cat}, which are favorable for low-resourced multilingual and crosslingual speech recognition.

For decoding, we build a weighted finite state transducer (WFST), obtained by composing the CTC topology, pronunciation lexicon and word-level n-gram language model, and use WFST-based decoding.

\section{Experiment}
\label{sec:exp}

\subsection{Experiment dataset and setup}
Our experiments are conducted on two datasets, CommonVoice \cite{ardila2020common} and AISHELL-1 \cite{bu2017aishell1}.
In our experiment, we use German, French, Spanish and Italian from CommonVoice to train the multilingual models. We carry out zero-shot and few-shot crosslingual experiments on Polish and Mandarin, where Polish comes from CommonVoice and Mandarin comes from AISHELL-1. Detailed data statistics are shown in Table \ref{tab:datainfo}.

\begin{table}[]
\centering
\caption{Datasets used in our experiments: the source, the number of IPA phone tokens in every language, the size of train, development and test sets in hours.}
\label{tab:datainfo}
\resizebox{0.48\textwidth}{!}{\begin{tabular}{cccccc}

\hline
Language           & Corpora  & \#Phones & Train & Dev & Test\\
\hline
German          & CommonVoice  & 40 & 639.4 & 24.7 & 25.1\\
French          & CommonVoice  & 57 & 465.2 & 21.9 & 23.0\\
Spanish       & CommonVoice  & 30 & 246.4 & 24.9 & 25.6\\
Italian        & CommonVoice  & 33 & 89.3 & 19.7 & 20.8\\
Polish   & CommonVoice  & 46 & 93.2 & 5.2 & 6.1\\
Mandarin           & AISHELL-1  & 96 & 150.9 & 18.1 & 10.0\\
\hline

\end{tabular}}
\end{table}
We employ Phonetisaurus \cite{novak-etal-2012-wfst}, a WFST-based G2P toolkit to generate IPA lexicons for the 6 languages in our experiments.
All the monolingual phones were mapped to IPA symbols and we merged the phones from German, French, Spanish and Italian to create the universal phone
set for multilingual training.

We use the CTC-CRF based ASR Toolkit - CAT \cite{an2020cat}, and will release the code in CAT when this work is published.
Unless otherwise stated, the acoustic models used in our experiments are all based on CTC-CRF, and word-level N-gram language models are trained on the training transcripts for each language.

In all experiments, 40 dimension filter bank with delta and delta-delta features are extracted as input to the AM, which is 3 blocks of VGG layers followed by a 3-layer BLSTM with 1024 hidden size (namely $H=2048$).
A dropout probability of 50\% is applied to the LSTM to prevent overfitting.
During training, we use Adam as optimizer, and set initial learning rate as 1e-3. When the performance on development set stops improving, learning rate is adjusted to 1/10 of the previous one until it is less than 1e-5.

\subsection{Experiment results}
Our experiments are divided into 2 parts, multilingual and (zero-shot and few-shot) crosslingual. The multilingual models trained on the collection of German, French, Spanish and Italian data are tested on these 4 languages for multilingual experiments and on Polish and Mandarin for crosslingual experiments.

\begin{table*}[]
\centering
\caption{Word error rate (WER) results (\%) for German, French, Spanish and Italian in the multilingual experiments.
Multilingual models are trained with 3 methods: the traditional method using flat phone embeddings (``Flat-Phone''), JoinAP with linear phone embeddings (``JoinAP-Linear''), and JoinAP with nonlinear phone embeddings (``JoinAP-Nonlinear'').
The multilingual models can be directly used without finetuning or with finetuning over the training data of the target languages.
Monolingual models are trained separately for comparisons.}
\label{tab:multi}
\begin{tabular}{cccccccc}
\hline
Language           & Flat-Phone  & Flat-Phone  & Flat-Phone & JoinAP-Linear & JoinAP-Linear & JoinAP-Nonlinear  & JoinAP-Nonlinear\\
                   &  monolingual  & w/o finetuning  & finetuning  & w/o finetuning & finetuning & w/o finetuning & finetuning \\
\hline
German          & 13.09  & 14.36 & 12.42 & 13.72 & 12.45 & 13.97 & 12.64\\
French          & 18.96  & 22.73 & 18.91 & 22.73 & 19.54 & 22.88 & 19.62\\
Spanish       & 15.11  & 13.93 & 13.06 &13.93 & 13.19 & 14.10 & 13.26\\
Italian        & 24.57  & 25.97 & 21.77 & 25.85 & 21.70 & 24.06 & 20.29\\
\hline
Average        & 17.93  & 19.25 & 16.54 & 19.06 & 16.72 & 18.75 & 16.45\\
\hline
\end{tabular}
\vspace{-3mm}
\end{table*}

\begin{table}[]
\centering
\vspace{-1mm}
\caption{About the intersections of the set of phones across languages.
For each phone in a language, we count how many languages it appears and define this count to the language-degree of this phone, which may take from 1 to 4. The cell in column $j$ denotes the number of those phones, whose language-degree is $j=1,2,3,4$.
}
\label{tab:overlapp}
\begin{tabular}{ccccc}
\hline
\diagbox{Language}{Language-degree}     & 4  & 3 & 2 & 1\\
\hline
German          & 18  & 6 & 8 & 8 \\
French          & 18  & 6 & 7 & 26\\
Spanish       & 18  & 4 & 1 & 7 \\
Italian        & 18  & 5 & 4 & 6\\
\hline
\end{tabular}
\vspace{-3mm}
\end{table}

\subsubsection{Multilingual experiment}

Multilingual results are summarized in Table \ref{tab:multi}.
Multilingual acoustic models are trained with 3 methods: the traditional method (namely using flat phone embeddings), JoinAP with linear phone embeddings, and JoinAP with nonlinear phone embeddings (the hidden layer size is 512). For each method, we test on the target language before and after fine-tuning over the data from the target language.
Monolingual models on German, French, Spanish and Italian are trained separately for comparisons. The main observations are as follows.

\emph{Without finetuning}, the trained multilingual model can be directly used and works as a single model. In this case, on average, both JoinAP-Nonlinear and  JoinAP-Linear perform better than Flat-Phone, and JoinAP-Nonlinear is the strongest. The average relative gain of JoinAP-Nonlinear over Flat-Phone is 3\%. But notably, the detailed improvements of JoinAP-Linear over Flat-Phone and of JoinAP-Nonlinear over JoinAP-Linear are in fact language-dependent.
For Italian, JoinAP-Nonlinear improves the most over JoinAP-Linear (7\%), while for other languages, JoinAP-Linear performs slightly better. JoinAP-Linear performs better or equally well, compared to Flat-Phone.
As observed in previous studies \cite{2020That,Heigold}, the performance differences between different multilingual training methods are affected by several factors, including the phonetic variety in this particular mix of multiple languages, data-scarce/data-rich for the target languages, etc.

\begin{figure*}[]
\centering
\centerline{\includegraphics[width=18cm]{fig3}}
\vspace{-3mm}
\caption{Visualization of Polish phone embeddings by t-SNE. (a) Flat phone embeddings, (b) JoinAP-Linear phone embeddings, (c) JoinAP-Nonlinear phone embeddings. They are obtained from the un-finetuned multilingual models in the zero-shot Polish experiment. Red circles indicate the consonants with the same manner of articulation, green circles indicate the consonants with the same place of articulation, and yellow circles indicate similar vowel height.}
\label{fig:tsne}
\vspace{-3mm}
\end{figure*}

\emph{After finetuing} over the entire data from the target language, we obtain separate models for each target language.
Similar to previous studies, the three multilingual training methods all significantly outperform monolingual trained models, on average.
JoinAP-Nonlinear reduces the average WER by 8\% against the monolingual models.
The performance differences between the three multilingual methods themselves become smaller, presumably because the target training data are already rich enough to train models. On average, JoinAP-Nonlinear still performs the strongest.

\emph{To analyze}, it is shown in Table \ref{tab:overlapp} how the four languages are intersected with each other.
We introduce the concept of the language-degree for a phone in multilingual training.
Language-degree 4 means that the phone is shared by all the 4 languages, there are 18 such phones. Language-degree 1 means that the phone is language-unique, belonging to only one language.
Italian has the smallest number of language-unique phones among the four languages. Many phones in Italian are also shared by other languages. Also note that Italian has the smallest amount of training data, as can be seen from Table \ref{tab:datainfo}.
These may explain the most significant benefit for Italian from multilingual training. For Italian, finetuned multilingual JoinAP-Nonlinear reduces the WER by 17\% again the monolingual Flat-Phone baseline. Also the gain by JoinAP-Nonlinear over JoinAP-Linear in Italian is also the largest (7\% without finetuning, 6\% after finetuning).
On the other hand, French has the largest number of language-unique phones among the four languages, and the training data size is larger.
This may explain the small improvement for French from multilingual training.

\begin{table}[]
\centering
\vspace{-1mm}
\caption{WER results (\%) for Polish in the crosslingual experiments. \#Finetune denotes the amount of data used in finetuning (0 means zero-shot).}
\label{tab:polish}
\begin{tabular}{cccc}

\hline
\#Finetune  & Flat-Phone & JoinAP-Linear & JoinAP-Nonlinear\\
\hline
0          & 33.15 & 35.73 & 31.80 \\
10 minutes          & 8.70  & 7.50 & 8.10\\
\hline
\end{tabular}
\vspace{-3mm}
\end{table}

\begin{table}[]
\centering

\caption{WER results (\%) for Mandarin in the crosslingual experiments.}
\label{tab:mandarin}
\begin{tabular}{cccc}

\hline
\#Finetune  & Flat-Phone & JoinAP-Linear & JoinAP-Nonlinear\\
\hline
0          & 97.10  & 89.51 & 88.41 \\
1 hour          & 25.39  & 25.21 & 24.86\\
\hline
\end{tabular}
\vspace{-3mm}
\end{table}

\vspace{-2mm}
\subsubsection{Crosslingual experiment}

Crosslingual results for Polish and Mandarin are summarized in Table \ref{tab:polish} and Table \ref{tab:mandarin} respectively.
The two languages are representative in how much the testing language is overlapped with the training languages, or say in the other way, how many unseen phones are in the testing language, as seen in Table \ref{tab:unique}. Polish represents the much overlapping setting, while Mandarin the less overlapping setting. The results for the two settings are different, as detailed below.

For Flat-Phone, in order to calculate the phone probabilities for unseen phones from the new languages (Polish and Mandarin), the parameters connecting to unseen phones in the output layer of the DNN model are initialized randomly.
For JoinAP-Linear and JoinAP-Nonlinear, it is straightforward to calculate the phone embeddings for unseen phones, according to Eq. (\ref{eq:embedding}) and Eq. (\ref{eq:nonlinear}), once we obtain the phonological-vectors for those unseen phones.

\emph{In the zero-shot setting}, for both Polish and Mandarin, JoinAP-Nonlinear outperforms both JoinAP-Linear and Phone-Flat significantly and consistently.
The JoinAP-Linear performs worse than Flat-Phone in Polish. This is somewhat unexpected, which may reflect some instability of JoinAP-Linear.

\emph{In the few-shot setting}, for both Polish and Mandarin, JoinAP-Nonlinear still yields much better results than Phone-Flat; however, the superiority of JoinAP-Nonlinear over JoinAP-Linear seems to be weakened, as there are more training data from the target languages.
The JoinAP-Nonlinear performs better than JoinAP-Linear in Mandarin, while not in Polish.
10 minutes of transcribed speech in Polish may be rich enough for JoinAP-Linear to be well adapted, as indicated by the low WER.
As can be seen from Table \ref{tab:unique}, the number of unseen phones in Polish is far less than in Mandarin. This may also explains the good performance of JoinAP-Linear in Polish.
Remarkably, under a large amount of finetuning data for a testing language that is much overlapped with training languages, say, 1 hour for Polish, the performances of different models will tend to saturate and become less differed. So we use 10-min finetuning data for Polish for comparing different models. 10-min for Mandarin will yield results similar to zero-shot, so we use 1-hour for Mandarin few-shot.

\begin{table}[t]
\centering
\vspace{-4mm}
\caption{Statistics about Polish and Mandarin, including the number of IPA phone tokens in every language, and the number of unseen phones.
}
\label{tab:unique}
\begin{tabular}{ccc}
\hline
Language  & \#Phones & \#Unseen phones\\
\hline
Polish         & 46  & 18  \\
Mandarin          & 96  & 79 \\
\hline
\end{tabular}
\vspace{-4mm}
\end{table}

\begin{table}[t]
\centering
\vspace{-5mm}
\caption{Detailed explanation of Fig. \ref{fig:tsne}. We list the IPA phones in the colored circles from different methods.}
\label{tab:tsne}
\begin{tabular}{c|ccc}

\hline
Method  & Color & Feature & Phones\\
\hline
\multirow{3}{*}{Flat}   &\multirow{2}{*}{Green} & Retroflex & \textrtailz\  \textrtaild\textrtailz\ t\textrtails\\
  & & Palatalized  &  \textscriptg\textsuperscript{j}\ k\textsuperscript{j}\ \textctc\textsuperscript{j}\ v\textsuperscript{j}\ b\textsuperscript{j}\ x\textsuperscript{j}\ p\textsuperscript{j}\  \\
                                        \cline{2-4}
                                        & Red & Fricative  & b\ t\ p\ d\ k\ \\
\hline
\multirow{8}{*}{Linear}   &\multirow{4}{*}{Green} & Alveolo-palatal & \textctz\ \textctc\ \textdctzlig\ \texttctclig\\
  & & Velar  & \textipa{N}\ \textscriptg\ k\ x\ \textscriptg\textsuperscript{j}\ k\textsuperscript{j}\ x\textsuperscript{j}  \\
  & & Alveolar  & \textdzlig\ \texttslig\ n\ d\ t\ r\ s\ z\ l  \\
  & & Retroflex  & \textrtails\ \textrtailz\  \textrtaild\textrtailz\ t\textrtails \\
                                          \cline{2-4}
                                          &\multirow{2}{*}{Red} & Plosive  & x\ v\ x\textsuperscript{j}\ v\textsuperscript{j}\ z\ s\ f\ \textrtailz \ \textrtails \\
& & Fricative & \textscriptg\ k\ p\ \textscriptg\textsuperscript{j}\ k\textsuperscript{j}\ p\textsuperscript{j}\ b\ b\textsuperscript{j}\ t\ d  \\
                                          \cline{2-4}
                                          &\multirow{2}{*}{Yellow}
& Close  &  i\ u\ w\ \textbari\ \~\textbari\\
 & & Open/Open-mid & a\ \textepsilon\ \textopeno\ \~\textopeno  \\
                                          \hline
\multirow{8}{*}{Nonlinear}&\multirow{3}{*}{Green} & Alveolo-palatal & \textctz\ \textctc\ \textdctzlig\ \texttctclig  \\
& & Velar  & \textipa{N}\ \textscriptg\ k\ x\ \textscriptg\textsuperscript{j}\ k\textsuperscript{j}\ x\textsuperscript{j}  \\
& & Alveolar  & n\ d\ t\ r\ s\ z\ l  \\

                                          \cline{2-4}
                                          &\multirow{3}{*}{Red} & Affricate  & \textdctzlig\ \texttctclig\ \textdzlig\ \texttslig  \\
& & Plosive  & x\ v\ x\textsuperscript{j}\ z\ s\ f  \\
& & Fricative & p\ p\textsuperscript{j}\ b\ b\textsuperscript{j}\ t\ d  \\
                                          \cline{2-4}
                                          &\multirow{2}{*}{Yellow}
& Close  &  i\ j\ \textbari\ \~\textbari\\
 & & Open/Open-mid & a\ \textepsilon\ \~\textepsilon\ \textopeno\ \~\textopeno  \\
\hline
\end{tabular}
\vspace{-5mm}
\end{table}

To further understand our phonological-vector based phone embeddings, we apply t-SNE \cite{tsne2008} to draw the 2048-dimensional phone embeddings on a 2-dimensional map. Fig. \ref{fig:tsne} shows the maps of the 46 phones in Polish, obtained from the un-finetuned multilingual models.
It seems that we can hardly find many sensible groupings for flat phone embeddings from Fig. \ref{fig:tsne}(a).
But for JoinAP-Linear and JoinAP-Nonlinear phone embeddings, the maps reflect more notable groupings, where similar phones are found to gather together in the maps. We use red, green and yellow circles to indicate the phones with the same manner of articulation, place of articulation and vowel height respectively. Their detailed IPA features are listed in Table \ref{tab:tsne}. The figures clearly show that the JoinAP based phone embeddings indeed carry phonological information, which could help zero-shot learning.
Moreover, it can be seen that the vowels are located in the top-right corner in Fig. \ref{fig:tsne}(c), while the vowels are separated in two corners in Fig. \ref{fig:tsne}(b). And the within-class scattering of (b) seems to be larger than (c). These observations could reflect the superority of JoinAP-nonlinear over JoinAP-Linear.

\section{Conclusion}
In this work, we propose the JoinAP method to join phonology driven phone embedding (top-down) and DNN based acoustic feature extraction (bottom-up).
We apply linear or nonlinear transformation of phonological-vectors to obtain phone embeddings, and compare to the traditional method using flat phone embeddings.
In the multilingual and crosslingual experiments, JoinAP-Nonlinear generally performs better than JoinAP-Linear and the traditional flat-phone method on average.
The improvements are generally the most significant for those target languages such as Italian in our multilingual experiments and Polish in our zero-shot crosslingual experiments, due to their data-scarce and high language-degrees of their phones (i.e., being well shared by other languages), and become weak for those target languages when they become data-rich such as French in our multilingual experiments and Polish in our few-shot crosslingual experiments.
In summary, the JoinAP method provides a principled approach to multilingual and crosslingual speech recognition.
Some promising directions include exploring DNN based phonological transformation, and pretraining over increasing number of languages.

\bibliographystyle{IEEEbib}

redpajama_set_name: RedPajamaArXiv


Celebrate Jim Morrison's Birthday With These Videos Of The Lizard King In Action [Watch] - Utter Buzz!
Born on this date in 1943, The Doors' Jim Morrison was one of the most iconic and influential front men in the history of rock music. Contributing hits like "Break On Through (To The Other Side)," "Light My Fire," "People Are Strange," and "L.A. Woman," Morrison was a special, yet eccentric talent.
Though his final years were marked by incident, most famously the March 1969 concert in Miami, FL when Morrison allegedly exposed himself to the crowd after trying to incite a riot, it cannot be understated the lasting effect Morrison has had on the generations that have followed. His powerful vocals and vulnerability have cemented his legacy with The Doors as one of the foremost gatekeepers of classic and psychedelic rock.
The post Celebrate Jim Morrison's Birthday With These Videos Of The Lizard King In Action [Watch] appeared first on L4LM.


When lazyloading images, one question that often arises is, "What should we use as placeholders?" Ideally the placeholder would fill the same space as the real image so that when it is loaded, the layout of the page doesn't reflow.
One technique (aside from using a generic placeholder) is to use Low Quality Image Placeholders (LQIP) to fill the space. Here, the placeholder is a really, really low-res version of the real image. It will be very small, and since it's based on the same image as the original, it will give the user an idea of what the image will be.
And although this can, and does, work, one of the drawbacks is the quality of this low-res image. If we compress a rasterized image as much as we can, we could possibly get down to at or under 1K. But in doing so, the image also ends up looking very coarse, with plenty of compression artifacts.
Another approach to get around this is to use an SVG for the placeholder, utilizing a Guassian Blur to smooth out the image. Tobias Baldauf has written about this technique, and has also released a tool called SQIP (SVG-based image placeholders) to help in creating these SVGs. The benefit of using SVGs is we can potentially get the size down to around the same size as the low-res JPEG, but by using blur, we can create a smoother looking image, while still providing the user some visual information about what's to come.
In this case, the SVG is right around 700 bytes, smaller than the low-quality JPEG, and smoother too.
So how do you use SQIP? It's quite easy. The main (only) requirement is Node.js 6+, and SQIP can be installed via NPM.
Once SQIP is installed, you can run it from the command line by specifying the image to convert, as well as other optional arguments.
In addition to the -o option (filename for output), there are a few other arguments you can supply. Depending on your needs, you may need to play around with them to tweak either the look or the size of output.
Note: SQIP also has a Node API mode that can be used. Options and examples are in the repo's README.
Overall, the tool was quite easy to install and use, and I'm thankful that it's available. Using SVGs for placeholders can be a great option when lazyloading images, and this tool makes that option all the more easier to implement.


In 1957 the extraordinary efforts of a group of architects and engineers transformed a bold concept into the Brick Breeden Fieldhouse, now a landmark and community gathering place on the Montana State University campus in Bozeman, Montana. Produced by Michael Ballard, KUSM-TV/MontanaPBS. Approx. 8 minutes in length.


text:
Ivanovskaya Lisitsa () is a rural locality (a selo) and the administrative center of Ivano-Lisichanskoye Rural Settlement, Grayvoronsky District, Belgorod Oblast, Russia. The population was 841 as of 2010. There are 7 streets.

Geography
Ivanovskaya Lisitsa is located 29 km north of Grayvoron (the district's administrative centre) by road. Kazachya Lisitsa is the nearest rural locality.

References

Rural localities in Grayvoronsky District

redpajama_set_name: RedPajamaWikipedia


I'm questioning my memory. No surprise there. In the shower, I often can't remember if I've shampooed yet or not. But this time, my faulty memory may have made me more critical of O'Neill than I needed.
In my last post about this book, I accused her of being inconsistent with her details. I'm not sure if this is necessarily so. Whereas I thought she had implied she had no childhood toys except a puppet (which was a problem for me as later she talks about a teddy bear she had since she was 6). Maybe this implication was not really made, maybe it was my own faulty conclusion. Simply because she hadn't mentioned other toys earlier, I assumed she had no others. This selective aspect of memory was illustrated quite often by O'Neill and it will no doubt be troublesome for other readers other than myself.
However, O'Neill would not be as much to blame as the reader. The more I reflected on it, the more I realized her portrayal of memory is probably more accurate than I've seen in other books. If you think about it, each time we recall memories of certain points in our lives, not all the details come flowing back each time. I might go on endlessly about cliff climbing when I was a child, recounting many zany and dangerous details. Yet the next time I bring it up might be the first time you've heard any account of my cousin and I throwing rocks down at a third friend who just wanted us to wait up. It's not that I made up additional details the second time around, it's just that maybe it was more relevant to the current circumstance the 2nd time around.
So when Baby talks about her months in Juvenile Detention and fails to mention her time doing solitude there, we needn't think it's a fault of the writing when it is mentioned further down the line. In hindsight, this reflection about memory (while being a secondary theme, for sure), was one of the many things I enjoyed about this book.
I also enjoyed the way O'Neill played with some of the assumptions we have about childhood and adulthood. Are adults necessarily more responsible? Maybe, maybe not. Most certainly have a clearer sense of what dangerous is, but that doesn't mean they know how to address it any better. Is childhood romance frivolous and insignificant? It certainly wasn't in Baby's case. In fact, her relationship with classmate Xavier was more real, substantial and precious than her relationship with the adult Alphonse. While childhood romances are rarely lasting, that doesn't mean they don't play an important role and have lasting impacts.
I wonder if people will find the ending a little too convenient. On the one hand, O'Neill doesn't give a "happily ever after" ending and does leave some ambiguity, but Alphonse's death and the sudden appearance of a cousin offering a helping hand could turn some people off. I'm not sure how I feel about it yet. Happy endings are possible of course, I'm not that cynical yet. If, and when, you read this book, I'd love to hear your thoughts.
Today on "Talking Books" they discussed Lullabies for Little Criminals. I didn't hear the entire show but amongst your updates, the praise I heard on CBC today, the enjoyment I got from her short story recently, and the fact that this book is being championed by my home-boy make me very eager to read it (right after Everything is Illuminated).
I will be sure to let you know my thoughts on it.
I hope O'Neill doesn't get too much attention leading up to Canada Reads. It'll put a target on her head for the other panelists for sure.
Good point! Samson was good at keeping A Complicated Kindness under the radar last year, but that might not work twice.


Robert Jenkins Onderdon -- The Fall of the Alamo or Crockett's Last Stand, 1903. Oil. The painting hangs in the governor's mansion in Austin, Texas. Courtesy of Friends of the Governor's Mansion.
Bob Thompson's fascination with Davy Crockett began in the family car, on a trip with his wife and two young daughters, listening to an old Burl Ives collection of folk songs — "Shoo Fly," "Big Rock Candy Mountain," and then a song that immediately grabbed the girls' attention.
"Born on a mountaintop in Tennessee, greenest state in the land of the free," Ives warbled. And when it ended, voices from the back seat insisted that dad play that song again.
That began a family immersion into all things Crockett, and more than a few surprises along the way. Finally, Thompson's need to separate fact from fiction, wild yarn — occasionally spun by Crockett himself — from the real David Crockett, led him on a meandering journey through much of the Southeast, up to Washington, D.C., and all the way to the Alamo.
An amiable, graceful writer and a thoroughly curious researcher, Thompson invites us along for the ride. Almost immediately, we learn that "The Ballad of Davy Crockett" isn't 100 percent true.
Crockett's official birthplace sits at the edge of the Nolichucky River in Tennessee, where it splashes down into a valley, and not on a mountaintop. But you can see the mountain from there.
And while Crockett loved hunting bear, he was much older than 3.
So what about that iconic image of Crockett decked out in buckskin? Unlikely, Thompson learns.
Even the great accolade "King of the Wild Frontier" is better attributed to Daniel Boone, according to the manager of the Davy Crockett Birthplace State Park.
Much of what passes for Crockett history in the current culture has its roots in film and TV. Walt Disney shaped a good bit of it in his three-part series on Crockett's life that hit the small screen in December 1954. The John Wayne movie The Alamo added to the legend. Crockett, a pretty fair amateur public relations man, gave them plenty to work with.
Born to an extremely poor family, the fifth of six sons, along with three daughters, he left home for the first time at 12, hired out by his father to help "a perfect stranger" to drive a herd of cattle, on foot, from eastern Tennessee to near Natural Bridge, Va., a trip of about 250 miles.
A year later, he left home again after a row with his father, this time for 2 1/2 years. He hired himself out, helping to drive a herd of cattle to northern Virginia, 400 miles away. From there, he was off to what is now West Virginia, and then to Baltimore, where he marveled at the tall ships, and thought of joining one bound for England.
Instead, he found his way home, 16 years old and so changed that his family didn't recognize him.
This would be a pattern for Crockett, who tried farming and milling and other businesses but couldn't resist an adventure and sure couldn't stay home.
His final temptation came from Texas, and he followed a stream of settlers from Tennessee and Kentucky who were heading west, looking for land.
Thompson spent a year on his quest, "my year of walking where Crockett walked," he writes. And along the way, he ran into a series of generous folks who patiently detailed Crockett's history in their part of the old frontier, although history might be better defined as local tradition.
The difficulty, Thompson found, is getting hard facts. There are some from Crockett's later years, especially his years in politics. Even his final great act, volunteering to fight for the Texans in their rebellion against Mexico, can be murky.
In movies and TV, Crockett is a powerful voice at the Alamo, telling tales with his usual bravado to keep spirits up, and then fighting with a particular ferocity, clubbing enemy soldiers with his long rifle, his ammunition long gone. But other accounts paint a far different end.
In the end, Thompson writes, Crockett's tale is both history and myth, and the trouble is separating the two.
Ultimately, it was Crockett himself who created his own persona, and his fans took that and ran.


text:
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Cement Plants located in Canada The Global Cement Report
Cement Plant Location Information for Canada. Cement plant locations and information on Canada can be found below. For full access to the database, purchase The Global Cement Report?, 12th Edition.
Canada | HeidelbergCement Group
The acquisition of the Italcementi Group in the second half of 2016 further strengthened HeidelbergCement鈥檚 presence in Canada with its subsidiary Essroc. Set up in 1866 as Coplay Cement, the company started producing cement in 1872. The name changed into Essroc in 1989.
LafargeHolcim upgrades cement plant in Canada to better
LafargeHolcim upgrades cement plant in Canada to better environmental performance 13 September 2016 Lafarge Canada Inc., a member of LafargeHolcim, has completed a project in Exshaw to modernize its cement plant while improving its environmental footprint.
Canada Cement industry news from Global Cement
Jul 26, 2019 路 Canada: Lafarge Canada has launched the first phase of its CO?MENT project. The objective is to build a full-cycle solution to capture and reuse CO 2 from a cement plant. The project is a partnership between Lafarge Canada, Inventys and Total. 鈥淟afargeHolcim is committed to reducing CO 2.
Canada Cement Jobs with Salaries
Cement Plant Labour. Company with Canada Cement jobs. The Quikrete Companies. The QUIKRETE? Companies is the largest manufacturer of packaged concrete and cement mixes in the U.S. and Canada. Jobs. Reviews (238) Salaries (309) For jobs in the United States, please visit.
Locations CRH Cement
CRH Canada and US is proud to provide cement to customers across Canada and in the US from our cement plants in Joliette, Qu茅bec and Mississauga, Ontario. The plants are supported by a broad distribution network of 14 terminals located across Canada and the US.
Update from Canada
Canada鈥檚 cement industry comprises 15 currently-active integrated cement plants, one ongoing project and one plant proposal. (See Figure 3). The active plants share 16.4Mt/yr of capacity, giving a national capacity utilisation figure of around 73% in 2016.
Cement Industry | The Canadian Encyclopedia
Dec 16, 2013 路 The next 2 largest producers, St Lawrence Cement Inc and St Marys Cement Co, combine to account for an additional 37% of Canadas capacity. Canadian cement plants tend to be modern and larger than other North American facilities.
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Our operations in the country started in 2001 and today include two well-established brands, St Marys Cement and Canada Building Materials (CBM). Toggle. Edit this item; Bowmanville plant in Ontario, Canada St Marys Cement has been supplying cement to the region for more than 100 years. Customers across Ontario know CBM for its specialized.
McInnis Cement project in Quebec sounds alarm bells in U.S
Nov 11, 2014 路 The fight over a $1.1-billion cement project in Quebecs Gasp茅 region is escalating as U.S. trade officials express concerns about the new plant at the World Trade Organization and backers charge.
Cement Plants located in United States The Global Cement
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Cement industry in the United States Wikipedia
The cement industry in the United States produced 82.8 million tonnes (81,500,000 long tons; 91,300,000 short tons) of cement in 2015, worth US$9.8 billion, and was used to manufacture concrete worth about US$50 billion. The US was the worlds third-largest producer of cement, after China and US cement industry includes 99 cement mills in 34 states, plus two plants in Puerto Rico.
Home | Lehigh Hanson Canada
Lehigh Hanson Canada Region. ABC Concrete. Allied Ready Mix Concrete. Cadman. Inland Aggregates. Inland Concrete. Inland Pipe. Lehigh Cement. Lehigh Materials. Mayco Mix. Ocean Concrete. Affiliate Plant. 6145 River Road Delta BC V4K 4E2 Canada. General (604) 324-8191. Affiliate Plant.
Cement Statistics and Information
Background Facts and Issues Concerning Cement and Cement Data OF-2005-1152; Historical Statistics for Mineral and Material Commodities in the United States Data Series 140 Cement; Materials in Use in U.S. Interstate Highways FS-2006-3127; Statistical Compendium; Links. American Coal Ash Association; Cement Association of Canada; European Cement.
Canadas cement industry is crumbling
Mar 07, 2016 路 Why Canada鈥檚 cement industry is crumbling Climate change rules and new competition are creating big problems for Canada鈥檚 cement industry by Peter Shawn Taylor. Mar 7, 2016.
Contact Us | Lafarge Canada
The cities where Canadians live, work, and raise their families along with the community鈥檚 infrastructure benefit from the solutions provided by Lafarge consisting of aggregates, asphalt and paving, cement, precast concrete, ready-mix concrete and road construction.
Canada. HeidelbergCement acquired its Canadian operations in 1993 and currently maintains a very strong position in the country with 4 modern cement plants, extensive aggregate deposits, and many ready-mixed concrete plants. Our Canadian cement production facilities, located in British Columbia, Alberta, Ontario, and Quebec (JV),.
Lafarge Canada Inc. is the country鈥檚 largest provider of solutions to the construction industry. With more than 6,000 employees, LafargeHolcim鈥檚 Canadian business produces and sells cement, ready-mix concrete, aggregates, asphalt, paving and construction, precast solutions and pipe products.
Serving North America for more than 100 years. CRH Canada and US is proud to provide cement to customers across Canada and in the US from our cement plants in Joliette, Qu茅bec and Mississauga, Ontario. The plants are supported by a broad distribution network of 14 terminals located across Canada and the US.
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Lafarge is Canadas largest provider of diversified construction materials and a member of the global group, LafargeHolcim. With 6,000 employees and 400 sites across Canada, our mission is to provide construction solutions that build better cities and communities. From cement and aggregates, to ready-mix and precast concrete as well as asphalt,.
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Lafarge Canada Inc. is Canadas largest cement company, with slightly less than one-third of the nations capacity. The next 2 largest producers, St Lawrence Cement Inc and St Marys Cement Co, combine to account for an additional 37% of Canadas capacity. Canadian cement plants tend to be modern and larger than other North American facilities.
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text:
Light in the gloom
IFR Asia - India 2013
India: Sowing the seeds of recovery
India's growth is stalling, the rupee is sliding and elections are looming, but there is still room for optimism.
Source: Reuters/Jitendra Prakash
A Hindu devotee lights an earthen lamp on the steps of Sindhiya Ghat during the Karthik Purnima and Dev Diwali festival in Varanasi.
While India is no longer a sure bet on rapid growth rates, the world's second most populated country is still home to sector-specific investment opportunities that offer value during periods of currency depreciation or low points in the business cycle.
India's recent macroeconomic woes are well documented. Since May, the rupee has slid 20% and political anxieties have festered, putting investors on watch and policymakers on crisis footing.
Although India's economic fundamentals remain stronger than the rupee exchange rate suggests, the economy as a whole is unlikely to return to double-digit growth anytime soon.
Global investors had tentatively retained their confidence in India's long-term economic prospects until Federal Reserve chairman Ben Bernanke began talking in May of tapering the US monetary stimulus, prompting a stampede out of emerging market assets.
Nonetheless, the future is not all doom and gloom for investors seeking returns in India's growth trajectory. Some sectors will benefit from a depreciation of the rupee, while demand in other sectors may override cyclical variations.
"The market pendulum has clearly swung from greed to fear," said Kunal Shroff, managing director at ChrysCapital, one of the largest India-focused funds with US$2.5bn in assets under management. "This will offer some great opportunities over the next one to two years to patient, long-term investors."
"People think there's been some massive structural deterioration when it's mainly a cyclical phenomenon."
Shroff said information technology, pharmaceuticals, consumer goods, and potentially, financial services were among the most attractive sectors. "Clearly export-orientated things work, especially IT and to some extent pharmaceuticals, which also works on the domestic side."
Indian assets have taken a particularly hard hit from worries that the Syrian crisis will drive up the costs of oil imports – now paid for in more expensive US dollars – coupled with uncertainty over state elections later this year, and national elections expected in April 2014.
Markets are now fixated on a negative feedback loop between the plummeting rupee and worsening fundamentals – including higher inflation, a rising fiscal deficit and the need to service higher dollar-denominated external debt.
Although a few sectors, such as IT and pharmaceuticals, stand to benefit from these woes, hope may also come from unusual sources – such as Mother Nature herself.
"So, what can happen? Look up to the gods, they've been kind this year and we've had good rains," said Dharmakirti Joshi, chief economist for Indian rating agency Crisil.
Strong monsoons should raise rural income, provide a mild push to rural demand, and, to some extent, moderate food price inflation. However, these trends would not be a cure-all for the Indian economy overall, Joshi warned.
"The outlook for the currency remains weak since agriculture alone cannot offset the headwinds coming from industry and the services sectors," Joshi said.
Cyclical versus structural
In the face of a seemingly endless flow of negative news and data, analysts have slashed Indian growth forecasts to the 4% or even 3% range.
Yet, Robert Prior-Wandesforde, director of Asian economics research at Credit Suisse, is holding firm for the moment with a 6% forecast, citing exaggerations on both sides of the equation: neither was India a structural miracle during the good times, nor is the economy in a state of collapse now.
"When you get a country with two or three years of unusually strong growth, particularly combined with low inflation, you get people proclaiming a structural miracle, but what is actually happening is a cyclical improvement," said Prior-Wandesforde.
He pointed out that such phenomena could be a function either of loose policy conditions, or of a market hitting the sweet spot of the economic cycle, with strong growth and low inflation.
"The opposite happens the other way around when growth is cyclically depressed for two or three years, as it has been in India," Prior-Wandesforde said. "People think there's been some massive structural deterioration when, again, it's mainly a cyclical phenomenon."
Prior-Wandesforde is not alone in seeing forecasts as being unusually vulnerable to distortion, especially in times of distress.
"Right now, there's too much noise in the system – too many moving parts," said Crisil's Joshi. "The danger is, when you extrapolate too much noise into your forecast, you mess up on both sides, with pessimism, as well as optimism."
While the troubled economic backdrop and currency weakness may cause Indian companies that rely on imported raw materials to suffer, other sectors may be set to outperform.
Exporters in industries that source inputs locally, such as IT, pharmaceuticals, and ready-made garments, should benefit from the rupee's devaluation, according to Joshi.
What is more, the depreciating rupee offers import substitution opportunities that target India's large and growing market of middle-class consumers. Indian companies can step into the crease and manufacture more goods currently sourced from China and other parts of Asia to sell in the country.
"The manufacture of mobile handsets can help India in a big way over the long term, as can production of consumer goods, such as toys, sunglasses, and footwear. India can obviously make more of these," said ChrysCapital's Shroff.
Of course, there is also the longstanding tradition of buying into the down cycle of an emerging market when it is affordable, in anticipation of an eventual rebound.
"We're not in the business of catching falling knives, but the unwinding creates a wonderful buying opportunity to invest in India, where valuations are cheap," said David Cornell, chief investment officer for Ocean Dial Asset Management, which focuses on Indian equities.
Ocean Dial's investment strategy rests on understanding the power of compounding. "You cross a certain income threshold, and the demand for certain products goes exponential," said Cornell. "So, a 25% increase in real income can show up as a sevenfold increase in the demand for certain products."
This phenomenon applies whether it is healthcare, consumer-related financial products – mortgages, loans, credit cards – or fast-moving consumer goods, especially those that cater to the rural consumer.
"These opportunities are not in the slightest affected by the current cyclical variations because they're irreversible," Cornell said.
Some of these opportunities may already be priced in, according to ChrysCapital's Shroff. He describes India as a "bipolar" equity market, with "other sectors not doing so well, such as infrastructure, where there are a lot of negatives – leverage, execution – that aren't easing anytime soon".
Three macroeconomic concerns – currency volatility, lack of global export competitiveness, and high interest rates – trouble Shroff. "The chances of short-term easing are looking less likely every day," he said.
Return of the rupee
If the rupee stabilises without the need for further rate hikes or more aggressive measures to defend the currency, some positive factors are likely kick in.
"Frankly, in any country where you see a 30% depreciation against the dollar, and large moves relative to regional currencies, you could see a bounce back," said Shroff.
What is more, India's current account deficit is narrowing, and the trade deficit has stabilised in recent months. A strong, stable source of support for its capital account has been a factor for India's success in attracting substantial deposits from overseas citizens, or non-resident Indians (NRIs).
Held either in dollar or rupee accounts, these have climbed substantially, from US$200m in fiscal year 2008 to US14.8bn in fiscal year 2013, close to the amount of foreign direct investment the country attracts annually.
Unlike "hot money" portfolio investments, which Royal Bank of Scotland forecasts will plummet to US$12bn in the current 2014 fiscal year, NRI deposits are expected to increase to US$16bn over the same period, and can be read as a vote of confidence in India's economic future.
Indian Finance Minister Palaniappan Chidambaram announced on August 26 the fast-tracking of US$28bn in stalled energy, infrastructure, and power projects, which should help to provide some stimulus to offset the currency-related slowdown.
"India wakes up when pushed to the wall," said Crisil's Joshi. "The government is serious. These projects need to be cleared and it's likely that at least some of them will be."
Investors can also look forward after the 2014 national election to the long-awaited adoption of a goods and services tax, although India's constitution must first be changed.
"A [GST] system would create a single common market in the country, one which hasn't existed so far, and would rationalise and reduce the burden of taxation across the supply chain," said Gaurav Kapur, senior economist in India for RBS.
Implementing a GST would also have fiscal benefits, boosting compliance and tax revenue for states and the central government. The increase in transparency could even lure more foreign investment.
An investor like Ocean Dial's Cornell believes the current woes may provide just the shock India needs. "The recent volatility is likely to be a good thing," Cornell said, "because it will lead politicians to undertake long overdue structural reforms."
However, in the end, government action is not required for individual Indian companies to succeed, and many will weather the current storm with or without it.
"Corporate India works, in spite of the government, not because of the government," Cornell said. "India has huge managerial depth and skill, both onshore and offshore. Given the difficulties they have to put up with, it's astonishing what they have managed to achieve."


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UNG Magazine
Summer enrollment increases at UNG
(Aug. 1, 2014) Preliminary figures show that the University of North Georgia (UNG) reported record enrollment for summer semester, with 5,853 students taking classes on the university's four campuses.
The figure, while still an unofficial tally, represents a 1.1 percent increase over summer 2013 enrollment of 5,791 students.
"The enrollment growth we continue to experience represents progress toward our goals of increasing educational opportunities and completion rates in the region," UNG President Bonita C. Jacobs said.
The summer enrollment figure includes students in UNG's Summer Language Institute (SLI), a six-week program that offers eight college credits in Arabic, Chinese, Korean, German, Russian, or Spanish. In addition to UNG students, SLI classes also include students from around the country who take courses at other colleges and universities during the regular academic year.
"Compared to normal semester courses, SLI is about 10 times more intense," said Darion Gibson, a UNG student taking the SLI Chinese course. "On top of the accelerated learning, we have more time to interact with the teachers and are able to grasp the concept of Chinese culture and history. Though it can be intimidating at times, it is extremely effective in helping us to learn the language and study skills. I think the program can prepare incoming freshmen and other college students extremely well for higher level language classes."
Many other students take summer courses to complete final requirements before graduation. UNG, which holds graduation ceremonies each semester, will hold commencement exercises on Saturday, Aug. 2 for some 200 graduates, representing about half of the some 400 degrees UNG will award this summer. The ceremony will be at 2 p.m. on UNG's Dahlonega Campus, and will honor graduates from all of UNG's four campuses. The university has selected Lynn Jackson, administrator of Northside Hospital-Forsyth, as commencement speaker. Tickets are required to attend the ceremony.
In recent years, many public colleges and universities across Georgia have recorded declining enrollment, but UNG has recorded a trend of steady growth. Created in January 2013 from the consolidation of Gainesville State and North Georgia College & State University, UNG has experienced significant growth in the past decade. That growth has continued post-consolidation, with UNG's enrollment approaching 16,000 students in 2013.
UNG's admission deadline for fall 2014 has been extended for programs on the Gainesville Campus. Students may still apply for admission to associate or bachelor's degree programs at that location.
Edie Rogers
Edie.Rogers@ung.edu
UNG Social Media Hub Subscribe to UNG Newsletter UNG News Archive
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November 20, 2013 Culture » Film
Matthew McConaughey is a tough but marvelous patient in Dallas Buyers Club
Pharm fight
By MaryAnn Johanson
Matthew McConaughey secures his non-rom-com credibility.
Could be that the very best thing about Dallas Buyers Club is that it instantly and effortlessly brushes aside any preconceived snarkery one might bring to it. You know, like how the lead actor's dramatic weight loss in preparation for portraying a dying man — in a based-on-a-sad-true-story issues drama, no less — is a sure bid for an Oscar nomination by a one-time rom-com actor.
If and when that Oscar bid comes, it'll be genuinely deserved. There is nothing showy or sentimental in Matthew McConaughey's rough-edged portrait of a small-minded man who learns the world is so much bigger than he ever wanted to accept. But there is enormous compassion, of the sort that seems to imply that McConaughey cares more about doing justice to a hard-to-like yet ultimately honorable man than he does about how he comes off as he's going about that task.
McConaughey's Ron Woodroof is a swaggering bigot when we meet him in early 1980s Texas. But an accident at work leads to a hospital visit, which leads to the discovery that not only is he HIV-positive, his AIDS is so far advanced that the doctors figure he's got maybe a month to live.
Two stories spin off from that moment, one personal and one political.
The personal is Woodroof's transformation from a guy who rejects the notion that he join an AIDS support group because it's for "fags" to a guy whose best friend and business partner is a transgender woman, Rayon (Jared Leto, who is magnificent here). Screenwriters Craig Borten and Melisa Wallack offer simple scenarios that smack Woodroof with the abrupt understanding his new reality brings, as when his gang of buddies suddenly treats him, literally, like an untouchable leper.
Director Jean-Marc Vallée neither embellishes these moments nor lingers on them. One scene, in which Woodroof comes to Rayon's defense in the middle of a supermarket, is over before we quite realize what an about-face it represents.
The political story is the deplorable reality of AIDS research at the time, and how Woodroof is forced to invent his own treatment with illegally imported drugs. That leads to him taking on the Food and Drug Administration, which becomes an accidental pushing for big changes in how AIDS is treated in the United States.
Woodroof's experience acquiring illegal recreational drugs helps him at first, and the same sorts of things that pot and coke dealers do — smuggling and selling on the sly — soon morph for Woodroof and Rayon into a sort of syndicate. Using "the Dallas Buyers Club," they can get around FDA restrictions on selling unapproved pharmaceuticals brought in from other countries. The idea is that you can give them away to club members who've paid a fee to join, but you can't sell them the drugs directly.
It's ridiculous, and that's the point. Dallas Buyers Club may be historical, but it does an excellent job of tapping into outrage over the state of healthcare in America, then and now, and suspicions about the FDA putting corporate profits above citizens' wellbeing. We may have gotten more enlightened as a culture about AIDS victims — a Ron Woodroof today would not be so casual about his (former) homophobia — but this story is far from a piece of pure history.
— scene@csindy.com
More Film »
Rated R - Drama
Rated R · 117 min. · 2013
Official Site: www.focusfeatures.com/dallas_buyers_club
Director: Jean-Marc Vallée
Cast: Matthew McConaughey, Jared Leto, Jennifer Garner, Steve Zahn and Dallas Roberts
Dallas Buyers Club is not showing in any theaters in the area.
Jennifer Lawrence doesn't reach full flame in The Hunger Games: Catching Fire
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The Wolf of Wall Street takes GoodFellas to the financial realm
Tags: Reviews, Dallas Buyers Club, Matthew McConaughey, HIV, AIDS, Jared Leto, Jean-Marc Vallee, Craig Borten, Melisa Wallack, Ron Woodroof
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You Are Here : Home / Culcairn /Our History
The district around Culcairn was originally settled by Europeans in 1834 having been the traditional home and hunting ground for the Wiradjuri Indigenous people up until that point.
The township of Culcairn was established in 1880 and became the hub for the railway system with rail lines through to Wagga Wagga, Albury, Holbrook and also to Corowa. The original Station Master's residence, built in 1882, is now a museum featuring the regions rich history. The construction of the Sydney to Melbourne railway saw the town grow significantly.
For its size, Culcairn has a large number of substantial heritage buildings including the Culcairn Hotel, Memorial Hall, Court House, Railway Station and Station Master's Residence.
One of the major landmarks of the town is the Culcairn Hotel. Built in 1891, the original building was extended in 1910 with the addition of an accommodation wing of over 70 rooms, stables, a coach house and extensive gardens. Patrons of the hotel could drive their coach or horse to Culcairn, stable it and catch the train to Sydney or Melbourne. The hotel boasted the town's first power supply in 1909.
Culcairn Museum Committee Station House
The Culcairn Museum Committee was formed at a public meeting in July, 1987. The Committee planned to restore the derelict c1893 Station Master's Residence to its original condition and furnish the house to reflect the period in which it was built.
Restoration of the Station House
Whilst the Station House was structurally sound, it had been vandalised and was in a state of disprepair. Its surrounds were overgrown and of poor appearance. The Committee was granted a 99 year lease of the property and funds were raised to enable urgent maintenance to be carried out.
Open Saturdays 10am to 4pm
and other days by appointment.
Bus trips, groups, schools, organisations are most welcome,
Admission donation.
For information and bookings contact:
Bruce Barkley, 02 6029 7568
Glenise Miller, 02 6029 8655
Follow this Link for further information.(PDF, 2MB)


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HomeIllinois NewsVargas: Why is Trump silent when America is winning?
Vargas: Why is Trump silent when America is winning?
By Mark Vargas -
Donald Trump became the Republican nominee for president of the United States by declaring that "America doesn't win anymore," and that he'll "Make America Great Again." But after watching the United States' performance at the Olympics in Rio, my message to Mr. Trump is simple: America is already great.
After two weeks of nonstop competition amongst eleven thousand athletes from around the world, the United States took home the gold in the Olympic medal count. One hundred and twenty-one total medals for Team USA. China, a country Mr. Trump claims is always beating the U.S., had a total of 70 Olympic medals. Team USA also beat China on the gold medal count, 46-26.
So with all this campaign rhetoric about how Mr. Trump will make America start winning again, where were those stubby little Twitter fingers during Team USA's two-week domination at the Olympics? Where were the late night tweets about beating China, or the congratulatory messages for Team USA?
Trump is clearly obsessed with winning. In fact, under a President Trump, we'll be winning so much that we'll get tired of it, he says. But when it came to Team USA doing all the winning in Rio — Trump was nowhere to be seen, or heard. A rarity for sure.
Trump has built his entire political brand on the idea that America isn't winning anymore. We're losers and we lose at everything. We lose to China on trade deals. Our political leaders are losers who aren't smart enough to make deals with other countries. We're not safe, nor are we great. We just don't win anymore.
This ideology is dangerous, deranged and demoralizing. And any candidate or future candidate who thinks this is a winning message — think again — you'll lose. And to the current candidates down ballot — I'm sorry. The traditional campaign playbook needs to be thrown out the window this election cycle. If you're going to survive this year, you're going to need to play by a whole new set of rules to rise above the divisiveness and win. America is already great, but together, we'll make it even greater.
The damage caused by Trump's rhetoric will take a Herculean effort to repair. It's like America is in an emotionally abusive relationship, with Mr. Trump as the abuser. We've heard the message a thousand times. We can't win and we're losers. But thanks to Team USA and our gold medal performance in Rio, we're reminded that we're anything but.
Not much can silence the almighty winner Trump — except when it's America that's doing all the winning.
Mark Vargas, a Judson College graduate, is a former GOP U.S. congressional candidate in Illinois and has advised world leaders, government officials and candidates on political messaging, issue advocacy and electoral campaign strategies. Follow him on Twitter at @MarkAVargas.
Rhoads: Blasphemy is NOT Funny, Ann
Foundation donors made up over half of Secretary Clinton's non-agency visitors
lee flanders August 23, 2016 At 12:42 pm
THE OLYMPICS , THE ECONOMY & THE RULE OF LAW ARE TOTALLY DIFFERENT ISSUES.
The Observer August 23, 2016 At 12:47 pm
It's simple, Mark.
There are idiots on the voter rolls, and many of them are on "Twitter," and on "Facebook" as well
Sports interests them, politics BORES them.
They pay attention to the athletes on the TV, but not to the government with it's hand in their pocket.
And Mark, if you don't believe we're losing, go to any big-box store and count the clothing products being made in America, and I think you will have a few fingers and toes left over after the count.
Live Free or Die August 23, 2016 At 1:55 pm
Does this idiot Vargas really think when trump made that statement it included the Olympics?? Trump was talking about trade deals, dealing with foreign countries, Obama paying ransom for Americans, etc… Trump was talking about politics, things that matter to the average Joe.
I watched about 5 minutes of the sporting events called the Olympics…. I couldn't have cared any less about it.
I care when American workers are screwed over by congress, when bad trade treaties are ratified, when Obama hides TPP so no one can read it all, I care when Obama give muslims a free pass into America without any vetting, I care when our criminal federal govt gives a free pass to the political elite and their rich friends, I care when Hillary gives foreign countries millions and millions of our tax dollars in return for a personal monetary favor, I care when illegal aliens are unlawfully given amnesty by Muslim Obama, I care when illegal aliens are allowed to bring illegal drugs into America… poisoning our children, I care when illegal aliens are getting tax credits they don't deserve, I care when illegal aliens are stealing jobs from American citizens, I care that the federal govt is nothing but organized crime and disobeys our Constitution, the law on a daily basis, I care when dirtbag Obama unlawfully uses Executive orders to effectively write law, etc…. I could go on for an hour! You get the point you stupid idiot Vargas!!
Joe August 23, 2016 At 3:05 pm
The country's marrying men. You must be as mentally deranged as those men, who want to marry men. You sound like a mini-Kinzinger, who won't even talk about marrying men anymore. Now, go back to Obama-worship you stupid Illinois Republican: http://www.realclearpolitics.com/docs/2016_Reuters_Tracking_-_Core_Political_8.17_.16_.pdf
Chase Gioberti August 23, 2016 At 3:51 pm
Sounds like Mark Vargas has no gripes with Hilary Clinton.
"Together, we'll make it even greater"
What a juvenile cliche. What have we produced in the last 15 years when we've been "united"? A quagmire in the Middle East in an ill advised war, the Patriot Act which most Americans now hate, the economic and budget breaking "stimulus" and Obamacare which most Americans now hate. If Americans are ever united watch out for what's about to happen to you.
Do these people even think things through before writing such sophomoric cliches?
Who cares about the Olympics? Vargas sounds like the type that would have loved the Gladiators in the Roman Coliseum while Rome crumbled around him.
If America is doing so great why does Vargas consider himself a Republican? Obviously he approves of the direction of the country under Obama.
concerned taxpayer August 23, 2016 At 8:35 pm
What a stupid article. Trump was NOT talking about the Olympics. He was talking about the U.S. being a laughing stock in the world arena, someone who is easily out maneuvered by Iran, Mexico, and Russia. Even Putin thinks Obama is a fool and easily manipulated. Mark, would you prefer to hear the lies Hillary tells about "how great Ameria is" when there are more people unemployed, more people on food stamps, more racial tension, more debt?
Mr H August 24, 2016 At 3:30 pm
Uh…. what kind of dumb thing is this?
I'd much rather be the best and richest country in the world economically than have ANY Olympic medals.
really August 25, 2016 At 9:14 am
GOP nominee Donald Trump on Wednesday presented a plan for granting undocumented immigrants legal status, the latest turn in his ever-evolving stance on immigration.


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Home Human Rights Iranian Authorities Pressure Elite Students For Televised Confessions
Iranian Authorities Pressure Elite Students For Televised Confessions
Iranian authorities pressure elite students to choose between televised confessions and the noose
For over four decades, Iranian authorities were exercising different kinds of torture and ill-treatment against political prisoners, protesters, prisoners of conscience, followers of religion and ethnic minorities with impunity. However, the progression of communicating devices and messaging apps shed light on what the ayatollahs, Pasdaran, members of the Revolutionary Guard (IRGC), and intelligence officers affiliated to the Ministry of Intelligence and Security (MOIS) are applying against inmates.
In a coordinated mission, judicial officials accommodate interrogators by attributing detainees' allegations to security crimes. Iran's judiciary annually issues hundreds of heavy sentences, such as long-term imprisonment and even the death penalty, for dissidents and protesters on repeated charges of "assembly and collusion against national security," "disrupting public order," and "moharebeh," meaning waging war against God, or."
These brutal punishments have ranked Iran as the record-holder of executions per capita. Since the beginning of 2020, under the notorious chief of judiciary Ebrahim Raisi, more than 100 prisoners have been hanged. Notably, in July 1988, the Islamic Republic founder Ruhollah Khomeini appointed Raisi as a key member of the "Death Commission," which led thousands of political prisoners to the gallows. According to the then deputy Intelligence Minister Reza Malek, authorities executed around 33,750 inmates in the summer of 1988.
On September 2, Amnesty International revealed new scopes of human rights violations inside Iran's dungeons and prisons. This non-profit organization mentioned that Iranian authorities use torture and other ill-treatment as a punishment. "Instead of investigating allegations of enforced disappearance, torture and other ill-treatment and other crimes against detainees, Iranian prosecutors became complicit in the campaign of repression by bringing national security charges against hundreds of people solely for exercising their rights to freedom of expression, association and peaceful assembly, while judges doled out guilty verdicts on the basis of torture-tainted 'confessions,'" said Diana Eltahawy, Amnesty International's Deputy Regional Director for the Middle East and North Africa.
Let's move on…
On April 10 of this year, two elite students Ali Younesi and Amir Hossein Moradi disappeared. Younesi, 20, is an award-winning computer science student at Tehran's Sharif Industrial University. He won the gold medal of the 12th International Olympiad on Astronomy and Astrophysics, held in China in 2018. Earlier, he had won gold and silver medals in the National Astronomy Olympiad in 2016 and 2017. Moradi is an award-winning physics student. He also won the Olympiad silver medal in 2017.
During his May 5 press conference, judiciary spokesperson Gholamhossein Esmaili eventually acknowledged to having apprehended the two and holding them in custody. He claimed that they had been detained for being affiliated to the Iranian opposition Mojahedin-e Khalq (MEK/PMOI).
The Iranian Regime Brutally Oppresses Students
Since that day, these elite students have endured excessive physical and psychological pressures. However, it seems that notorious interrogators have yet to succeed in raising the required allegations against them. Therefore, they recently began practicing a new round of torture: pushing them to make televised confessions.
"On Wednesday (September 2), my brother, Ali Younesi, was told to accept allegations in televised confessions to have his death sentence commuted to life imprisonment. After five months of detention, torture in solitary confinement, and general interrogations, he has been under pressure and threats for three weeks to agree to a televised interview," tweeted Aida Younesi on September 5.
دقیقه ۱:۴۰صحبتهاى آقای ابراهیمی رو ببينيد. همين حرف رو روز چهارشنبه به برادرم #علي_يونسى گفتند که با اعتراف تلويزيوني اتهامات رو قبول کن تا اعدامت رو بکنیم حبس ابد. بعد از ۵ماه بازداشت، شكنجه، انفرادی و بازجویی عمومی، ٣هفته است كه با تهدید و فشار اصرار بر مصاحبه تلویزیونی دارند. https://t.co/IypaLHWXLm
— Aida Younesi آیدا یونسی (@YounesiAida) September 5, 2020
Before the revelation made by Aida Younsei, authorities had attempted to lure her brother into televised confessions by claiming he would be meeting with Mattias Lentz, the Swedish ambassador to Tehran. In this respect, Reza, brother to Ali Younesi, revealed the authorities' attempts to obtain enforced confessions.
"My brother, Ali Younesi, has been detained for 150 days now. He was held in solidarity confinement for two months (of which 20 days he was in a 2.5 square meter room with no windows). Last week, interrogators tried to deceive Ali by offering him a visit to the Sweden Embassy in Tehran and a conversation with the Swedish ambassador and other diplomats. Ali refused and said he would not attend any such meeting until he has access to a lawyer of his own choosing," Reza Younesi tweeted on September 7.
Last week, interrogators tried to deceive Ali with offering him to visit Sweden Embassy in Tehran and have a conversation with the Swedish ambassador & some other diplomats. Ali refused and said he will not attend any meeting until he has access to own lawyer. @AmnestySverige
— Reza Younesi رضا يونسى (@RezaYounesi) September 7, 2020
"I have informed the Swedish Ministry of Foreign Affairs that Iran's intelligence service lied in claiming the Swedish ambassador would meet Ali in the Swedish embassy in Iran to actually obtained coerced confessions and footage for a televised confession. Although the deception of 'meeting with Swedish diplomats' did not succeed, they are still using threats and deception to extract a televised confession. They have threatened that if Ali and Amirhossein do not confess, they will receive heavy sentences in court," he explained.
Although the deception of "meeting w/ Swedish diplomats" did not succeed, they are still using threats & deception to make televised confession. They have threatened that if Ali & his friend do not confess, they will receive heavy sentences in court. @KerstinLundgren @MCederfelt
Notably, in recent months, the authorities have more frequently used coerced confessions to raise allegations against detainees. On August 5, the Iranian government executed Mostafa Salehi for participating in late 2017-early 2018 protests. However, harrowing torture compelled him to admit to crimes he had not committed to ending his suffering. Judiciary officials filed his confessions as evidence and used it to have him executed.
In other cases, authorities sentenced to death nine protesters detained in August 2018 based on coerced confessions. National wrestling champion Navid Afkari is among them. The Iranian judiciary is claiming he had killed a security agent while it previously had sentenced another person and executed him for the same charges.
Iran's Inhuman Judiciary
In fact, Iranian authorities try to terrify the society by practicing excessive pressures on elites. In this respect, as the Iranian people continue their struggle for fundamental freedoms, civil rights, justice, equality, and the rule of law, the international community must compel the Iranian government to abolish the execution sentences and free all political prisoners, including protesters detained in recent protests.
Iranian political prisoners
Previous articleSummary of Repression and Human Rights Violations in Iran—August 2020
Next articleCalling Justice for Victims of 1988 Massacre in Iran
Iranian Opposition Calls for Ending Death Penalty
Iranian Authorities Commit Permanent Torture with Amputation
Iran Resistance Calls for International Action to Save Political Prisoners


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Q: How to read files with specific type of files from subfolders of a directory in JAVA i want to ask how its possible to read files with (.xxx) type from subfolders that exist in a direcory.
I have a folder that contains subfolders (the number of the subfolders isn't known)
  C:\MainFolder
  contains->           [subFolder_A][subFolder_B]......[subFolder_n]

Every subFolder containts plenty of files but one of them has a different type, specifically a (.fingerprint) type.
       [subFolder_A]  -->  a.txt , atitle.txt  , afin.fingerprint
       [subFolder_B]  -->  b.txt , btitle.txt  , bfin.fingerprint
             ...............................................
       [subFolder_n]  -->  n.txt , ntitle.txt  , nfin.fingerprint

So i want to read each time one of this file to java ...do some functions and then the next one until the C:\MainFolder is fulled scan.
I can read one if i give the path directly to code but i want some tips if anyone knows to take them all with an auto way
        Path path = Paths.get("C:\\MainFolder\\afin.fingerprint");
        byte[] data;
        byte[] fin;
        try {
             this.data = Files.readAllBytes(path);
             byte[] data = Files.readAllBytes(path);
       } catch (Exception e) {....}
          fin=data;

A: You can walk the file tree recursively with a stream, for example like this:
 Files.walk(Paths.get("C:/MainFolder"))
      .filter(p -> p.toFile().isFile())
      .filter(p -> p.getFileName().toString().endsWith(".fingerprint"))
      .forEach(p -> process(p));

A: You can loop through the subdirectories like this:
File directory = new File(//path to directory);
  for(File subdirectory : directory.listFiles()){
    for(File file : Subdirectory.listFiles()){
      if(file.toString().endsWith(".footprint"){
      //doStuff
    }
  }
}

A: You can find all the subfolders of main folder and scan them in a loop. And for each subfolder, again, You can find all files in it and then filter them as You wish.
For listing contents of a folder use
https://docs.oracle.com/javase/7/docs/api/java/io/File.html#listFiles()

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API Fire
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President Trump's New NSA Could Help Drain the Swamp
by Andrew R. Kloster | Sep 19, 2019
Like most of the president's MAGA base, I was pulling for Col. Douglas Macgregor to replace John Bolton as National Security Adviser (NSA). It seemed the perfect opportunity for the president to select an NSA who fully supported his instincts…
What Is the Trump Doctrine?
by Jed Babbin | Sep 16, 2019
The most accurate measure of a man is who he counts as his friends and who he counts as his enemies. John Bolton has a lot of friends and allies in the American national security community, myself included. When Bolton…
Trump's Carrot-and-Stick Middle East Policy
by Daniel Krygier | Sep 13, 2019
President Donald Trump's recent firing of his national security advisor John Bolton (or acceptance of Bolton's resignation) has raised speculation that the Trump administration is changing course on foreign policy and security. Some pundits have suggested that the White House could…
Trump Seeks Fresh Face for Security Post
by Roger Kaplan | Sep 11, 2019
John Bolton, the mustachioed "hard-liner" who replaced H. R. McMaster as President Donald Trump's National Security Advisor last year, was thanked for his service Monday and told to haul ass. His response was to send word via Twitter — a…
A Revealing Realignment in the Trump Administration
by John Jiang | Jul 2, 2019
Donald Trump surprised the world on Sunday when he arrived on the Korean peninsula for a meeting with Kim Jong-un, becoming the first sitting U.S. president to set foot in North Korea. The 45-minute meeting ended with a promise to…
Iran: More Failures From U.S. Intelligence
by Brandon J. Weichert | May 23, 2019
"In this land, the man who gives victory in battle is prized beyond every other man," or so says Prince Feisal as portrayed by Sir Alec Guinness in the epic 1962 biopic, Lawrence of Arabia. Okay, so Feisal's quote is…
So, You Want to Invade Iran?
Recently, the Trump Administration announced that it was deploying both an American aircraft carrier as well as B-52 bombers to the Middle East as a show of force against the Iranians. According to National Security Adviser John Bolton, intelligence provided…
Iran's Kakistocracy at Forty
by Jed Babbin | Feb 11, 2019
This week marks the fortieth anniversary of Iran's 1979 revolution. Since the late Ayatollah Ruhollah Khomeini took power, the Iranian regime has worked diligently to spread its malignancy around the world. Its influence has spread throughout the Middle East, South…
Fire Bolton
by F.H. Buckley | May 26, 2018
Do you remember the story of the dog in the manger? It's an old Greek myth. A dog lies in the manger, surrounded by hay. The dog can't eat hay. Only horses eat hay. But the dog won't let the…
Trump's Veto Threat Is Latest Act in White House Drama
by Debra J. Saunders | Mar 25, 2018
Washington In past White Houses, the removal of a national security adviser would be the culmination of much drama and handwringing. Yet President Donald Trump's decision Thursday to replace H.R. McMaster with former U.N. Ambassador John Bolton was only Act…