Speech dataset resources

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 8 different voices. 4 of them have a British accent and the 4 others with American accent.	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	Total Duration: 5.04h Language: EN Speech Style: spontaneous conversation Audio parameters: 16 kHz, 16 bits, mono Recording Equipment: Telephony Recording Environment: Indoor Environment
Europarl-ASR			Creative Commons Attribution 4.0 License.	• Language: English	• Gonçal V. Garcés Díaz-Munío • Joan Albert Silvestre-Cerdà
TED-LIUM 3				Language: English 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 Access: freely available for the research community

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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.