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arXiv · 1906.01199

Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation

Elizabeth Salesky·Matthias Sperber·Alan W Black
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Abstract

Previous work on end-to-end translation from speech has primarily used frame-level features as speech representations, which creates longer, sparser sequences than text. We show that a naive method to create compressed phoneme-like speech representations is far more effective and efficient for translation than traditional frame-level speech features. Specifically, we generate phoneme labels for speech frames and average consecutive frames with the same label to create shorter, higher-level source sequences for translation. We see improvements of up to 5 BLEU on both our high and low resource language pairs, with a reduction in training time of 60%. Our improvements hold across multiple data sizes and two language pairs.

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Elizabeth Salesky, Matthias Sperber, Alan W Black. 2019-06-04. Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation. https://arxiv.org/abs/1906.01199

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