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Update files from the datasets library (from 1.3.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.3.0

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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bin.* filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ annotations_creators:
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+ - expert-generated
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+ language_creators:
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+ - found
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+ languages:
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+ - en
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+ licenses:
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+ - other-public-domain
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - other
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+ task_ids:
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+ - other-other-automatic-speech-recognition
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+ - other-other-text-to-speech
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+ ---
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+
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+ # Dataset Card for lj_speech
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+ - [Contributions](#contributions)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [The LJ Speech Dataset](https://keithito.com/LJ-Speech-Dataset/)
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+ - **Repository:** [N/A]
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+ - **Paper:** [N/A]
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+ - **Leaderboard:** [Paperswithcode Leaderboard](https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech)
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+ - **Point of Contact:** [Keith Ito](mailto:[email protected])
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+
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+ ### Dataset Summary
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+
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+ This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours.
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+
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+ The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded in 2016-17 by the LibriVox project and is also in the public domain.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ The dataset can be used to train a model for Automatic Speech Recognition (ASR) or Text-to-Speech (TTS).
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+ - `other:automatic-speech-recognition`: An ASR model is presented with an audio file and asked to transcribe the audio file to written text.
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+ The most common ASR evaluation metric is the word error rate (WER).
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+ - `other:text-to-speech`: A TTS model is given a written text in natural language and asked to generate a speech audio file.
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+ A reasonable evaluation metric is the mean opinion score (MOS) of audio quality.
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+ The dataset has an active leaderboard which can be found at https://paperswithcode.com/sota/text-to-speech-synthesis-on-ljspeech
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+
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+ ### Languages
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+
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+ The transcriptions and audio are in English.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A data point comprises the path to the audio file, called `file` and its transcription, called `text`.
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+ A normalized version of the text is also provided.
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+
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+ ```
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+ {
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+ 'id': 'LJ002-0026',
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+ 'file': '/datasets/downloads/extracted/05bfe561f096e4c52667e3639af495226afe4e5d08763f2d76d069e7a453c543/LJSpeech-1.1/wavs/LJ002-0026.wav',
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+ 'text': 'in the three years between 1813 and 1816,'
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+ 'normalized_text': 'in the three years between eighteen thirteen and eighteen sixteen,',
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+ }
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+ ```
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+
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+ Each audio file is a single-channel 16-bit PCM WAV with a sample rate of 22050 Hz.
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+
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+ ### Data Fields
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+
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+ - id: unique id of the data sample.
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+
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+ - file: a path to the downloaded audio file in .wav format.
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+
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+ - text: the transcription of the audio file.
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+
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+ - normalized_text: the transcription with numbers, ordinals, and monetary units expanded into full words.
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+
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+ ### Data Splits
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+
106
+ The dataset is not pre-split. Some statistics:
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+
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+ - Total Clips: 13,100
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+ - Total Words: 225,715
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+ - Total Characters: 1,308,678
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+ - Total Duration: 23:55:17
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+ - Mean Clip Duration: 6.57 sec
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+ - Min Clip Duration: 1.11 sec
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+ - Max Clip Duration: 10.10 sec
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+ - Mean Words per Clip: 17.23
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+ - Distinct Words: 13,821
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+
118
+ ## Dataset Creation
119
+
120
+ ### Curation Rationale
121
+
122
+ [Needs More Information]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ This dataset consists of excerpts from the following works:
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+
130
+ - Morris, William, et al. Arts and Crafts Essays. 1893.
131
+ - Griffiths, Arthur. The Chronicles of Newgate, Vol. 2. 1884.
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+ - Roosevelt, Franklin D. The Fireside Chats of Franklin Delano Roosevelt. 1933-42.
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+ - Harland, Marion. Marion Harland's Cookery for Beginners. 1893.
134
+ - Rolt-Wheeler, Francis. The Science - History of the Universe, Vol. 5: Biology. 1910.
135
+ - Banks, Edgar J. The Seven Wonders of the Ancient World. 1916.
136
+ - President's Commission on the Assassination of President Kennedy. Report of the President's Commission on the Assassination of President Kennedy. 1964.
137
+
138
+ Some details about normalization:
139
+ - The normalized transcription has the numbers, ordinals, and monetary units expanded into full words (UTF-8)
140
+ - 19 of the transcriptions contain non-ASCII characters (for example, LJ016-0257 contains "raison d'être").
141
+ - The following abbreviations appear in the text. They may be expanded as follows:
142
+
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+ | Abbreviation | Expansion |
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+ |--------------|-----------|
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+ | Mr. | Mister |
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+ | Mrs. | Misess (*) |
147
+ | Dr. | Doctor |
148
+ | No. | Number |
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+ | St. | Saint |
150
+ | Co. | Company |
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+ | Jr. | Junior |
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+ | Maj. | Major |
153
+ | Gen. | General |
154
+ | Drs. | Doctors |
155
+ | Rev. | Reverend |
156
+ | Lt. | Lieutenant |
157
+ | Hon. | Honorable |
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+ | Sgt. | Sergeant |
159
+ | Capt. | Captain |
160
+ | Esq. | Esquire |
161
+ | Ltd. | Limited |
162
+ | Col. | Colonel |
163
+ | Ft. | Fort |
164
+ (*) there's no standard expansion for "Mrs."
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+
166
+ #### Who are the source language producers?
167
+
168
+ [Needs More Information]
169
+
170
+ ### Annotations
171
+
172
+ #### Annotation process
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+
174
+ - The audio clips range in length from approximately 1 second to 10 seconds. They were segmented automatically based on silences in the recording. Clip boundaries generally align with sentence or clause boundaries, but not always.
175
+ - The text was matched to the audio manually, and a QA pass was done to ensure that the text accurately matched the words spoken in the audio.
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+
177
+ #### Who are the annotators?
178
+
179
+ Recordings by Linda Johnson from LibriVox. Alignment and annotation by Keith Ito.
180
+
181
+ ### Personal and Sensitive Information
182
+
183
+ [Needs More Information]
184
+
185
+ ## Considerations for Using the Data
186
+
187
+ ### Social Impact of Dataset
188
+
189
+ [Needs More Information]
190
+
191
+ ### Discussion of Biases
192
+
193
+ [Needs More Information]
194
+
195
+ ### Other Known Limitations
196
+
197
+ - The original LibriVox recordings were distributed as 128 kbps MP3 files. As a result, they may contain artifacts introduced by the MP3 encoding.
198
+
199
+ ## Additional Information
200
+
201
+ ### Dataset Curators
202
+
203
+ The dataset was initially created by Keith Ito and Linda Johnson.
204
+
205
+ ### Licensing Information
206
+
207
+ Public Domain ([LibriVox](https://librivox.org/pages/public-domain/))
208
+
209
+ ### Citation Information
210
+
211
+ ```
212
+ @misc{ljspeech17,
213
+ author = {Keith Ito and Linda Johnson},
214
+ title = {The LJ Speech Dataset},
215
+ howpublished = {\url{https://keithito.com/LJ-Speech-Dataset/}},
216
+ year = 2017
217
+ }
218
+ ```
219
+
220
+ ### Contributions
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+
222
+ Thanks to [@anton-l](https://github.com/anton-l) for adding this dataset.
dataset_infos.json ADDED
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+ {"main": {"description": "This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading \npassages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length \nfrom 1 to 10 seconds and have a total length of approximately 24 hours.\n\nNote that in order to limit the required storage for preparing this dataset, the audio\nis stored in the .wav format and is not converted to a float32 array. To convert the audio\nfile to a float32 array, please make use of the `.map()` function as follows:\n\n\n```python\nimport soundfile as sf\n\ndef map_to_array(batch):\n speech_array, _ = sf.read(batch[\"file\"])\n batch[\"speech\"] = speech_array\n return batch\n\ndataset = dataset.map(map_to_array, remove_columns=[\"file\"])\n```\n", "citation": "@misc{ljspeech17,\n author = {Keith Ito and Linda Johnson},\n title = {The LJ Speech Dataset},\n howpublished = {\\url{https://keithito.com/LJ-Speech-Dataset/}},\n year = 2017\n}\n", "homepage": "https://keithito.com/LJ-Speech-Dataset/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "file": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "normalized_text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "file", "output": "text"}, "builder_name": "lj_speech", "config_name": "main", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4667022, "num_examples": 13100, "dataset_name": "lj_speech"}}, "download_checksums": {"https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2": {"num_bytes": 2748572632, "checksum": "be1a30453f28eb8dd26af4101ae40cbf2c50413b1bb21936cbcdc6fae3de8aa5"}}, "download_size": 2748572632, "post_processing_size": null, "dataset_size": 4667022, "size_in_bytes": 2753239654}}
dummy/main/1.1.0/dummy_data.zip ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:fbc98fcaf43b89df9c4c4e218613298edc79211af75c3fa516ec31ef35020db6
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+ size 74086
lj_speech.py ADDED
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1
+ # coding=utf-8
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+ # Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """LJ automatic speech recognition dataset."""
18
+
19
+ from __future__ import absolute_import, division, print_function
20
+
21
+ import csv
22
+ import os
23
+
24
+ import datasets
25
+
26
+
27
+ _CITATION = """\
28
+ @misc{ljspeech17,
29
+ author = {Keith Ito and Linda Johnson},
30
+ title = {The LJ Speech Dataset},
31
+ howpublished = {\\url{https://keithito.com/LJ-Speech-Dataset/}},
32
+ year = 2017
33
+ }
34
+ """
35
+
36
+ _DESCRIPTION = """\
37
+ This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading
38
+ passages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length
39
+ from 1 to 10 seconds and have a total length of approximately 24 hours.
40
+
41
+ Note that in order to limit the required storage for preparing this dataset, the audio
42
+ is stored in the .wav format and is not converted to a float32 array. To convert the audio
43
+ file to a float32 array, please make use of the `.map()` function as follows:
44
+
45
+
46
+ ```python
47
+ import soundfile as sf
48
+
49
+ def map_to_array(batch):
50
+ speech_array, _ = sf.read(batch["file"])
51
+ batch["speech"] = speech_array
52
+ return batch
53
+
54
+ dataset = dataset.map(map_to_array, remove_columns=["file"])
55
+ ```
56
+ """
57
+
58
+ _URL = "https://keithito.com/LJ-Speech-Dataset/"
59
+ _DL_URL = "https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2"
60
+
61
+
62
+ class LJSpeech(datasets.GeneratorBasedBuilder):
63
+ """LJ Speech dataset."""
64
+
65
+ VERSION = datasets.Version("1.1.0")
66
+
67
+ BUILDER_CONFIGS = [
68
+ datasets.BuilderConfig(name="main", version=VERSION, description="The full LJ Speech dataset"),
69
+ ]
70
+
71
+ def _info(self):
72
+ return datasets.DatasetInfo(
73
+ description=_DESCRIPTION,
74
+ features=datasets.Features(
75
+ {
76
+ "id": datasets.Value("string"),
77
+ "file": datasets.Value("string"),
78
+ "text": datasets.Value("string"),
79
+ "normalized_text": datasets.Value("string"),
80
+ }
81
+ ),
82
+ supervised_keys=("file", "text"),
83
+ homepage=_URL,
84
+ citation=_CITATION,
85
+ )
86
+
87
+ def _split_generators(self, dl_manager):
88
+ root_path = dl_manager.download_and_extract(_DL_URL)
89
+ root_path = os.path.join(root_path, "LJSpeech-1.1/")
90
+ wav_path = os.path.join(root_path, "wavs/")
91
+ csv_path = os.path.join(root_path, "metadata.csv")
92
+
93
+ return [
94
+ datasets.SplitGenerator(
95
+ name=datasets.Split.TRAIN, gen_kwargs={"wav_path": wav_path, "csv_path": csv_path}
96
+ ),
97
+ ]
98
+
99
+ def _generate_examples(self, wav_path, csv_path):
100
+ """Generate examples from an LJ Speech archive_path."""
101
+
102
+ with open(csv_path, encoding="utf-8") as csv_file:
103
+ csv_reader = csv.reader(csv_file, delimiter="|", quotechar=None, skipinitialspace=True)
104
+ for row in csv_reader:
105
+ uid, text, norm_text = row
106
+ filename = f"{uid}.wav"
107
+ example = {
108
+ "id": uid,
109
+ "file": os.path.join(wav_path, filename),
110
+ "text": text,
111
+ "normalized_text": norm_text,
112
+ }
113
+ yield uid, example