End-to-end Automatic Speech Translation of Audiobooks
Table 1: Size of the Augmented LibriSpeech and BTEC corpora, with the average frame, character and word counts (subword count for LibriSpeech) per segment. Character counts take whitespaces into account. The source side of BTEC actually has six times this number of segments and hours, because we concatenate multiple speakers (synthetic voices). LibriSpeech train 1 (alignments) and train 2 (automatic translation) share the same source side.
['Corpus', 'Corpus', 'Total segments', 'Total hours', 'Source (per segment) frames', 'Source (per segment) chars', 'Source (per segment) (sub)words', 'Target (per segment) chars']
Augmented LibriSpeech contains 236 hours of speech in total, which is split into 4 parts: a test set of 4 hours, a dev set of 2 hours, a clean train set of 100 hours, and an extended train set with the remaining 130 hours. The test, dev and train sets correspond to the highest rated alignments. The remaining data (extended train) is more noisy, as it contains more incorrect alignments. The test set was manually checked, and incorrect alignments were removed. We perform all our experiments using train only (without extended train). Furthermore, we double the training size by concatenating the aligned references with the Google Translate references.