In a conventional CAT (Computer Assisted Translation) system a human translator post-edits an automatically generated target language text using the keyboard. In this paper we extend a CAT system with speech input by which the translator speaks the translation, a process refered to as sight translation. We report several experiments to improve the performance of an automatic speech recognition system, taking advantage of machine translation output and information fromWordNet. Overall we outperform a baseline system which has no semantic information by an increased 1.6% word accuracy for the English to Hindi translation.
|Publication status||Published - 2013|
|Event||10th International Conference on Natural Language Processing - Centre for Development of Advanced Computing, Noida, India|
Duration: 18 Dec 2013 → 20 Dec 2013
Conference number: 10
|Conference||10th International Conference on Natural Language Processing|
|Location||Centre for Development of Advanced Computing|
|Period||18/12/2013 → 20/12/2013|
Bibliographical noteCBS Library does not have access to the material
Tammewar, A., Singla, K., Bangalore, S., & Carl, M. (2013). Enhancing ASR by MT using Semantic Information from HindiWordNet. Poster session presented at 10th International Conference on Natural Language Processing, Noida, India.