IBM Mastor: Multilingual Automatic Speech-To-Speech Translator
Yuqing Gao, Bowen Zhou, Liang Gu, Ruhi Sarikaya, Hong-Kwang Jeff Kuo, A.-V.I. Rosti, Mohamed A. Afify, Weizhong Zhu · 2006
In this paper, we describe the IBM MASTOR systems which handle spontaneous free-form speech-to-speech translation on both laptop and hand-held PDAs. Challenges include speech recognition and machine translation in adverse environments, lack of data and linguistic resources for under-studied languages, and the need to rapidly develop capabilities for new languages. Importantly, the code and models must fit within the limited memory and computational resources of hand-held devices. 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).