Abstract
In this paper, we study the incorporation of statistical machine translation models to automatic speech recognition models in the framework of computer-assisted translation. The system is given a source language text to be translated and it shows the source text to the human translator to translate it orally. The system captures the user speech which is the dictation of the target language sentence. Then, the human translator uses an interactive-predictive process to correct the system generated errors. We show the efficiency of this method by higher human productivity gain compared to the baseline systems: pure ASR system and integrated ASR and MT systems.- Anthology ID:
- 2012.iwslt-papers.13
- Volume:
- Proceedings of the 9th International Workshop on Spoken Language Translation: Papers
- Month:
- December 6-7
- Year:
- 2012
- Address:
- Hong Kong, Table of contents
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Note:
- Pages:
- 237–243
- Language:
- URL:
- https://aclanthology.org/2012.iwslt-papers.13
- DOI:
- Cite (ACL):
- Shahram Khadivi and Zeinab Vakil. 2012. Interactive-predictive speech-enabled computer-assisted translation. In Proceedings of the 9th International Workshop on Spoken Language Translation: Papers, pages 237–243, Hong Kong, Table of contents.
- Cite (Informal):
- Interactive-predictive speech-enabled computer-assisted translation (Khadivi & Vakil, IWSLT 2012)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2012.iwslt-papers.13.pdf