Our principle objective was to reduce the error rate of speech recognition systems used by professional translators. Our work concentrated on Spanish-to-English translation. In a baseline study we estimated the error rate of an off-the-shelf recognizer to be 9.98%. In this paper we describe two independent methods of improving speech recognizers: a machine translation (MT) method and a topic-based one. An evaluation of the MT method suggests that the vocabulary used for recognition cannot be completely restricted to the set of translations produced by the MT system and a more sophisticated constraint system must be used. An evaluation of the topic-based method showed significant error rate reduction, to 5.07%.
Ludovik, Yevgeny and Ron Zacharski. 2000. MT and topic-based techniques to enhance speech recognition systems for professional translators. Proceedings of CoLing 2000, 1061-1065. Saarbrücken, July 31-August 4, 2000. (pdf)