Modelling prosodic and dialogue information for automatic speech recognition
The main goal of the work presented in this thesis, is to provide a system for automatically classifying utterances into different types known as moves. In order to do this, one can take advantage of certain constraints found in natural dialogues. Utterances of the same type follow each other with a degree of regularity. This study joins together these three aspects to perform automatic move detection, which is used in an automatic speech recognition system to constrain the possible number of words. This system is successful in identifying utterances types and subsequently reduces the word error rate of the recogniser. It also provides an in depth study into how people express the discourse function of an utterance through intonation and provides a unique model of dialogue structure.
Wright, Helen Frances
Modelling prosodic and dialogue information for automatic speech recognition. The main goal of the work presented in this thesis, is to provide a system for automatically classifying utterances into different types known as moves. In order to do this, one can take advantage of certain constraints found in natural dialogues. Utterances of the same type follow each other with a degree of regularity. This study joins together these three aspects to perform automatic move detection, which is used in an automatic speech recognition system to constrain the possible number of words. This system is successful in identifying utterances types and subsequently reduces the word error rate of the recogniser. It also provides an in depth study into how people express the discourse function of an utterance through intonation and provides a unique model of dialogue structure.
modelling prosodic dialogue information automatic_speech recognition main_goal work_present provide system automatically classify utterance different_type know move order take_advantage certain constraint find natural dialogue utterances type follow degree regularity study join together aspect perform automatic move detection use automatic_speech recognition system constrain possible number word system successful identifying utterance type subsequently reduces word error rate recogniser also_provide depth_study people express discourse function utterance intonation provide_unique model_dialogue structure