Speech dataset resources: Difference between revisions

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|LibriSpeech
|LibriSpeech
|audio books (clean)
|Audio books (clean, flac format)
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* Text is converted into upper-case, removed punctuation, expanding common abbreviations and non-standard words
* Text is converted into upper-case, removed punctuation, expanding common abbreviations and non-standard words.
* The transcriptions are aligned and segmented automatically.  
* The transcriptions are aligned and segmented automatically.  
|Creative Commons Attribution 4.0 International License.  
|Creative Commons Attribution 4.0 International License.  
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* The dataset is split into 3 sections with 100.6, 363.6, 496.7 hours of speech
* Language: English
* The gender ratio of speakers is about half and half.  
 
* The dataset is split into 3 sections with 100.6, 363.6, 496.7 hours of speech.
* The gender ratio of speakers is about half and half.
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* Dataset is made by Vassil Panayotov.  
* Dataset is made by Vassil Panayotov.  

Revision as of 09:36, 27 September 2023

This table summarizes dataset resources available

Note: You have editing rights to the table, so you can edit/adjust it to your needs*. Your instructors will clean it up afterwards.

Dataset name Type of data Annotation remarks License Metadata Name/s of people who are entering the data
LibriSpeech Audio books (clean, flac format)
  • Text is converted into upper-case, removed punctuation, expanding common abbreviations and non-standard words.
  • The transcriptions are aligned and segmented automatically.
Creative Commons Attribution 4.0 International License.
  • Language: English
  • The dataset is split into 3 sections with 100.6, 363.6, 496.7 hours of speech.
  • The gender ratio of speakers is about half and half.
  • Dataset is made by Vassil Panayotov.
  • Guoguo Chen , Daniel Povey , Sanjeev Khudanpur are also contributed to the dataset and article below.
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x
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* this means: you may also add additional pages and link to them in this table

Notes on LibriSpeech

  • We only used the development set to test our ASR code in Python;
  • The names of the speakers who recorded all the audiobooks contained in this corpus are also available in a separate text file;
  • Exhaustive information about this dataset can be found in this article;
  • This dataset was included in the Kaldi speech recognition toolkit.