Using intonation to constrain language models in speech recognition
Paul M. Taylor, Simon King, Stephen D. Isard, Helen Wright, Jacqueline C. Kowtko · 1997
This paper describes a method for using intonation to reduce word error rate in a speech recognition system designed to recognise spontaneous dialogue speech. We use a form of dialogue analysis based on the theory of conversational games. Different move types under this analysis conform to different language models. Different move types are also characterised by different intonational tunes. Our overall recognition strategy is first to predict from intonation the type of game move that a test utterance represents, and then to use a bigram language model for that type of move during recognition. 1 INTRODUCTION This paper describes a method for using intonation to reduce word error rate in a speech recognition system designed to recognise spontaneous dialogue speech. Our experiments are on the DCIEM Maptask corpus [2], a corpus of spontaneous task-oriented dialogue speech. Our dialogue analysis is based on the theory of conversational games first introduced by Power [9] and adapted for ...