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.- Anthology ID:
- P19-1179
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1835–1841
- Language:
- URL:
- https://aclanthology.org/P19-1179
- DOI:
- 10.18653/v1/P19-1179
- Cite (ACL):
- Elizabeth Salesky, Matthias Sperber, and Alan W Black. 2019. Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1835–1841, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation (Salesky et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/P19-1179.pdf