We introduce a new collection of spoken English audio suitable for training
speech recognition systems under limited or no supervision. It is derived from
open-source audio books from the LibriVox project. It contains over 60K hours
of audio, which is, to our knowledge, the largest freely-available corpus of
speech. The audio has been segmented using voice activity detection and is
tagged with SNR, speaker ID and genre descriptions. Additionally, we provide
baseline systems and evaluation metrics working under three settings: (1) the
zero resource/unsupervised setting (ABX), (2) the semi-supervised setting (PER,
CER) and (3) the distant supervision setting (WER). Settings (2) and (3) use
limited textual resources (10 minutes to 10 hours) aligned with the speech.
Setting (3) uses large amounts of unaligned text. They are evaluated on the
standard LibriSpeech dev and test sets for comparison with the supervised
state-of-the-art.

提供了一个适用于有限或无监督语音识别训练的口语英语音频集合，其中包含来自 LibriVox 项目的开源有声读物，已使用语音活动检测进行段分割，并标记有 SNR，说话者 ID 和流派描述，同时提供了基线系统和评估指标，分为三个设置进行评估。