Self-Training for End-to-End Speech Translation

Pino Juan
Pino Juan
Xu Qiantong
Xu Qiantong
Dousti Mohammad Javad
Dousti Mohammad Javad
Tang Yun
Tang Yun

INTERSPEECH, pp. 1476-1480, 2020.

Cited by: 0|Views11
EI

Abstract:

One of the main challenges for end-to-end speech translation is data scarcity. We leverage pseudo-labels generated from unlabeled audio by a cascade and an end-to-end speech translation model. This provides 8.3 and 5.7 BLEU gains over a strong semi-supervised baseline on the MuST-C English-French and English-German datasets, reaching st...More

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