Pretraining by backtranslation for end-to-end ASR in low-resource settings

Matthew Wiesner; Adithya Renduchintala; Shinji Watanabe; Chunxi Liu; Najim Dehak; Sanjeev Khudanpur

doi:10.21437/Interspeech.2019-3254

Pretraining by backtranslation for end-to-end ASR in low-resource settings

Matthew Wiesner, Adithya Renduchintala, Shinji Watanabe, Chunxi Liu, Najim Dehak, Sanjeev Khudanpur

Research output: Contribution to journal › Conference article

Abstract

We explore training attention-based encoder-decoder ASR in low-resource settings. These models perform poorly when trained on small amounts of transcribed speech, in part because they depend on having sufficient target-side text to train the attention and decoder networks. In this paper we address this shortcoming by pretraining our network parameters using only text-based data and transcribed speech from other languages. We analyze the relative contributions of both sources of data. Across 3 test languages, our text-based approach resulted in a 20% average relative improvement over a text-based augmentation technique without pretraining. Using transcribed speech from nearby languages gives a further 20-30% relative reduction in character error rate.

Original language	English
Pages (from-to)	4375-4379
Number of pages	5
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume	2019-September
DOIs	https://doi.org/10.21437/Interspeech.2019-3254
Publication status	Published - 2019
Externally published	Yes
Event	20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 - Graz, Austria Duration: 2019 Sep 15 → 2019 Sep 19

Keywords

Encoder-decoder
Low-resource
Multi-modal data augmentation
Multilingual ASR
Pretraining

ASJC Scopus subject areas

Language and Linguistics
Human-Computer Interaction
Signal Processing
Software
Modelling and Simulation

Access to Document

10.21437/Interspeech.2019-3254

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Wiesner, M., Renduchintala, A., Watanabe, S., Liu, C., Dehak, N., & Khudanpur, S. (2019). Pretraining by backtranslation for end-to-end ASR in low-resource settings. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2019-September, 4375-4379. https://doi.org/10.21437/Interspeech.2019-3254

Pretraining by backtranslation for end-to-end ASR in low-resource settings. / Wiesner, Matthew; Renduchintala, Adithya; Watanabe, Shinji; Liu, Chunxi; Dehak, Najim; Khudanpur, Sanjeev.

In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Vol. 2019-September, 2019, p. 4375-4379.

Research output: Contribution to journal › Conference article

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