Paper: Integration Of Speech To Computer-Assisted Translation Using Finite-State Automata

ACL ID P06-2061
Title Integration Of Speech To Computer-Assisted Translation Using Finite-State Automata
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

State-of-the-art computer-assisted transla- tion engines are based on a statistical pre- diction engine, which interactively pro- vides completions to what a human trans- lator types. The integration of human speech into a computer-assisted system is also a challenging area and is the aim of this paper. So far, only a few methods for integrating statistical machine transla- tion (MT) models with automatic speech recognition (ASR) models have been stud- ied. They were mainly based on N- best rescoring approach. N-best rescor- ing is not an appropriate search method for building a real-time prediction engine. In this paper, we study the incorporation of MT models and ASR models using finite-state automata. We also propose some transducers based on MT models for rescoring the ASR word graphs....