Samsung’s System for the IWSLT 2019 End-to-End Speech Translation Task
Tomasz Potapczyk, Pawel Przybysz, Marcin Chochowski, Artur Szumaczuk
Abstract
This paper describes the submission to IWSLT 2019 End- to-End speech translation task by Samsung R&D Institute, Poland. We decided to focus on end-to-end English to German TED lectures translation and did not provide any submission for other speech tasks. We used a slightly altered Transformer architecture with standard convolutional layer preparing the audio input to Transformer en- coder. Additionally, we propose an audio segmentation al- gorithm maximizing BLEU score on tst2015 test set.- Anthology ID:
- 2019.iwslt-1.12
- Volume:
- Proceedings of the 16th International Conference on Spoken Language Translation
- Month:
- November 2-3
- Year:
- 2019
- Address:
- Hong Kong
- Editors:
- Jan Niehues, Rolando Cattoni, Sebastian Stüker, Matteo Negri, Marco Turchi, Thanh-Le Ha, Elizabeth Salesky, Ramon Sanabria, Loic Barrault, Lucia Specia, Marcello Federico
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2019.iwslt-1.12
- DOI:
- Cite (ACL):
- Tomasz Potapczyk, Pawel Przybysz, Marcin Chochowski, and Artur Szumaczuk. 2019. Samsung’s System for the IWSLT 2019 End-to-End Speech Translation Task. In Proceedings of the 16th International Conference on Spoken Language Translation, Hong Kong. Association for Computational Linguistics.
- Cite (Informal):
- Samsung’s System for the IWSLT 2019 End-to-End Speech Translation Task (Potapczyk et al., IWSLT 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2019.iwslt-1.12.pdf
- Data
- MuST-C