Answers.Body: <p>The tutorials you link are not much relevant, there are already existing implementations of your exact problem.</p>
  
  <p>You can use <a href="https://github.com/swshon/dialectID_e2e" rel="nofollow noreferrer">https://github.com/swshon/dialectID_e2e</a>, there are many other similar implementations on github.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-04-13T21:17:52.507Z
Answers.Text: Can you explain more how they are not relevant? Thank you.
Answers.UserDisplayName: Abdulkader
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-04-13T21:20:03.273Z
Answers.Text: You can use those things too, they are just not as related as the project I linked you.
Answers.UserDisplayName: Nikolay Shmyrev
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-04-13T20:58:33.217Z
Answers.LastActivityDate: 2019-04-13T20:58:33.217Z
Answers.UserDisplayName: Nikolay Shmyrev
Body: <p>In <a href="https://www.tensorflow.org/tutorials/sequences/audio_recognition" rel="nofollow noreferrer">this</a> tutorial, they build a speech recognition model to classify a one-second audio clip as one of ten predefined words. Suppose that we modified this problem as the following: Given an Arabic dataset, we aim to build a <em>dialects</em> recognition model to classify a <em>two</em>-second audio clip as one of <span class="math-container">$n$</span> local dialects using ten predefined <em>sentences</em>. I.e. for each of these ten sentences, there are <span class="math-container">$x$</span> different phrases and idioms which refer to the same meaning<span class="math-container">$^*$</span>. Now how can I take advantage of the mentioned tutorial to solve the modified problem?</p>
  
  <p><span class="math-container">$*$</span> The <span class="math-container">$x$</span> different phrases and idioms for each sentence are not predefined.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-03-09T09:46:29.523Z
Comments.Text: Is my modified problem similar to this [one](https://arxiv.org/ftp/arxiv/papers/1707/1707.09917.pdf)?
Comments.UserDisplayName: Abdulkader
Tags: <deep-learning><natural-language-processing><classification><voice-recognition>
Title: How much the dialects recognition and speech recognition are relevant?
UserDisplayName: Abdulkader
ThreadText: # How much the dialects recognition and speech recognition are relevant?
  
  (Asked by: username_0 on 2019-03-09)
  
  In [this](https://www.tensorflow.org/tutorials/sequences/audio_recognition) tutorial, they build a speech recognition model to classify a one-second audio clip as one of ten predefined words. Suppose that we modified this problem as the following: Given an Arabic dataset, we aim to build a *dialects* recognition model to classify a *two*-second audio clip as one of $n$ local dialects using ten predefined *sentences*. I.e. for each of these ten sentences, there are $x$ different phrases and idioms which refer to the same meaning$^\*$. Now how can I take advantage of the mentioned tutorial to solve the modified problem?
  
  $\*$ The $x$ different phrases and idioms for each sentence are not predefined.
  
  **Tags:** deep-learning, natural-language-processing, classification, voice-recognition
  
  > **Comments:**
  > **username_0**: Is my modified problem similar to this [one](https://arxiv.org/ftp/arxiv/papers/1707/1707.09917.pdf)?  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-04-13. Score: 1 | Accepted answer
  
  The tutorials you link are not much relevant, there are already existing implementations of your exact problem.
  
  You can use <https://github.com/swshon/dialectID_e2e>, there are many other similar implementations on github.
  
  > **Comments:**
  > **username_0**: Can you explain more how they are not relevant? Thank you.  
  > **username_1**: You can use those things too, they are just not as related as the project I linked you.  
  
  ---
  
  