11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Improving Speech Synthesis of Machine Translation Output

Alok Parlikar, Alan W. Black, Stephan Vogel

Carnegie Mellon University, USA

Speech synthesizers are optimized for fluent natural text. However, in a speech to speech translation system, they have to process machine translation output, which is often not fluent. Rendering machine translations as speech makes them even harder to understand than the synthesis of natural text. A speech synthesizer must deal with the disfluencies in translations in order to be comprehensible and communicate the content. In this paper, we explore three synthesis strategies that address different problems found in translation output. By carrying out listening tasks and measuring transcription accuracies, we find that these methods can make the synthesis of translations more intelligible.

Full Paper

Bibliographic reference.  Parlikar, Alok / Black, Alan W. / Vogel, Stephan (2010): "Improving speech synthesis of machine translation output", In INTERSPEECH-2010, 194-197.