Speech dataset resources: Difference between revisions

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• Joan Albert Silvestre-Cerdà
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Revision as of 13:29, 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.
Hugging Face
LibriVoxDeEn Audio based on audio books (.wav file format)

German text and English translation (.tsv file format)

Creative Commons Attribution 4.0 Non-Commercial ShareAlike Internation License
  • German audio and transcription, with English translation.
  • >100 hours of audio material and >50k parallel sentences.
  • Quality of audio and text has been evaluated manually.
https://github.com/jim-schwoebel/voice_datasets
SPEECH-COCO Creative Commons Attribution 4.0 International Liscence
  • Language: English
  • This corpus contains 616,767 spoken captions from MSCOCO's val2014 and train2014 subsets (respectively 414,113 for train2014 and 202,654 for val2014).
  • William Havard, Laurent Besacier, Olivier Rosec
SAF (Short Answer Feedback Dataset) based on audio books (.wav
  • CC BY-SA
ASR-ETELECSC WAV (PCM)

TXT (UTF-8)

MAGIC DATA

OPEN-SOURCE LICENSE

5.04 hours of transcribed English conversational speech beyond telephony
Europarl-ASR Creative Commons Attribution 4.0 License. • Language: English • Gonçal V. Garcés Díaz-Munío

• Joan Albert Silvestre-Cerdà

TED-LIUM 3
  • Language: English
  • Data source: TED conference videos (format: sphere)
  • Transcription: Yes ( format: stm)
  • Duration: 452 hrs
  • Number of talkers: 1938 (Male: 1303; Female: 635)
  • Alignments: cover around 83.0% of audio; 3.2M words

*) 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.