The IBM speech-to-speech translation system for smartphone: Improvements for resource-constrained tasks

  • Authors:
  • Bowen Zhou;Xiaodong Cui;Songfang Huang;Martin Cmejrek;Wei Zhang;Jian Xue;Jia Cui;Bing Xiang;Gregg Daggett;Upendra Chaudhari;Sameer Maskey;Etienne Marcheret

  • Affiliations:
  • IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, United States

  • Venue:
  • Computer Speech and Language
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes our recent improvements to IBM TRANSTAC speech-to-speech translation systems that address various issues arising from dealing with resource-constrained tasks, which include both limited amounts of linguistic resources and training data, as well as limited computational power on mobile platforms such as smartphones. We show how the proposed algorithms and methodologies can improve the performance of automatic speech recognition, statistical machine translation, and text-to-speech synthesis, while achieving low-latency two-way speech-to-speech translation on mobiles.