Quantitative and qualitative information about the training datasets is displayed in Tables 13 and 14
respectively. A detailed description of the training datasets is presented below.
People’s Speech (Galvez et al., 2021) is a large-scale English speech recognition dataset which
assembles audio-transcription pairs sourced from the internet. The dataset covers multiple sources,
including interviews, radio and finance. We use the “clean” subset of the dataset, with approximately
12,000 hours of training data and corresponding validation and test splits.
GigaSpeech (Chen et al., 2021) is a multi-domain speech recognition corpus curated from audio-
books, podcasts and YouTube. It contains both narrated and spontaneous speech over a range of
content material, including science, arts and sports. We use the large subset (2,500 hours) to train
and the standard validation and test splits.
Common Voice (Ardila et al., 2020) is a collection of open-license, crowd-source speech datasets
DISTIL-WHISPER