Abstract

Conventional approaches to speech-to-speech (S2S) translation typically ignore key contextual information such as prosody, emphasis, discourse state in the translation process. Capturing and exploiting such contextual information is especially important in machine-mediated S2S translation as it can serve as a complementary knowledge source that can potentially aid the end users in improved understanding and disambiguation. In this work, we present a general framework for integrating rich contextual information in S2S translation. We present novel methodologies for integrating source side context in the form of dialog act (DA) tags, and target side context using prosodic word prominence. We demonstrate the integration of the DA tags in two different statistical translation frameworks, phrase-based translation and a bag-of-words lexical choice model. In addition to producing interpretable DA annotated target …

Date

2013

Authors

Vivek Kumar Rangarajan Sridhar, Srinivas Bangalore, Shrikanth Narayanan

Journal

Computer Speech & Language

Volume

27

Issue

2

Pages

492-508

Publisher

Academic Press