IBM MASTOR System: Multilingual Automatic Speech-To-Speech Translator

نویسندگان

  • Yuqing Gao
  • Bowen Zhou
  • Ruhi Sarikaya
  • Mohamed Afify
  • Hong-Kwang Kuo
  • Wei-Zhong Zhu
  • Yonggang Deng
  • Charles Prosser
  • Wei Zhang
  • Laurent Besacier
چکیده

In this paper, we describe the IBM MASTOR, a speech-to-speech translation system that can translate spontaneous free-form speech in real-time on both laptop and hand-held PDAs. Challenges include speech recognition and machine translation in adverse environments, lack of training data and linguistic resources for under-studied languages, and the need to rapidly develop capabilities for new languages. Another challenge is designing algorithms and building models in a scalable manner to perform well even on memory and CPU deficient hand-held computers. We describe our approaches, experience, and success in building working free-form S2S systems that can handle two language pairs (including a low-resource language).

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تاریخ انتشار 2006