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Dataset Overview

Dataset Type

ASR Speech Corpus

Language

English

Speech Style

Spontaneous conversation and reading

Content

Various topics

Audio Parameters

16kHz, 16 bit, mono

File Format

OPUS

Recording Equipment

Various equipment

Recording Environment

Various environment

License

Popular Datasets

ASR Corpus

Giga Speech

GigaSpeech : An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

Dataset Overview

Dataset Type

ASR Speech Corpus

Language

English

Speech Style

Spontaneous conversation and reading

Content

Various topics
16kHz, 16 bit, mono

File Format

OPUS

Recording Equipment

Various equipment

Recording Environment

Various environment

License

GigaSpeech, prepared and released by SpeechColab, is an evolving, multi-domain English
speech recognition corpus with 10,000 hours of high quality labeled
audio suitable for supervised training, and 33,000 hours of total audio suitable for semi-supervised and unsupervised training. Around 33,000 hours of transcribed audio is first collected from audiobooks, podcasts and YouTube, covering both read and spontaneous speaking styles,and a variety of topics, such as arts, science, sports, etc. A new forced alignment and segmentation pipeline is proposed to create sentence segments suitable for speech recognition training, and to filter out segments with low-quality transcription.

For system training, GigaSpeech provides five subsets of different sizes, 10h, 250h, 1000h, 2500h, and 10000h. For our 10,000-hour XL training subset, we cap the word error rate at 4% during the filtering/validation stage, and for all our other smaller training subsets, we cap it at 0%. The DEV and TEST evaluation sets, on the other hand, are re-processed by professional human transcribers to ensure high transcription quality.


For details of how we created the dataset, please refer to our Interspeech paper: “GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio”. Preprint available on arxiv (https://arxiv.org/abs/2106.06909).

Please also check out our Github repository for applications and leaderboard (https://github.com/SpeechColab/GigaSpeech).

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