Fisher (Cieri et al., 2004a) is a corpus of two-sided conversational telephone calls amongst speakers
from the United States. We combine Part 1 (Cieri et al., 2004b;c) and Part 2 (Cieri et al., 2005a;b)
of the dataset to give 1,960 hours of training data.
LibriSpeech (Panayotov et al., 2015) is a standard dataset for training and evaluating academic
speech models. It is comprised of 960 hours of narrated audiobooks sourced from the LibriVox2
project. The audiobook domain provides high-quality recording conditions, with little to no back-
ground noise. We use the standard split of train, validation (dev-clean, dev-other) and test sets
(test-clean, test-other).
VoxPopuli (Wang et al., 2021) is a large-scale multilingual speech datasets consisting of European
Parliament event recordings from 2009-2020. The speech is oratory and from the political domain,
with mostly non-native speakers. We use the English subset with approximately 550 hours and
dataset splits provided therein.
DISTIL-WHISPER