SRI collected a corpus to study how spontaneous speech differs from other types of speech. The corpus was collected in two parts: (1) a spontaneous Switchboard-style conversation on an assigned topic, and (2) a reading session in which participants read transcripts of their conversation from part 1. Experiments were conducted on sentences with identical transcripts that varied in speaking style. The word-error rates varied from 29% (careful dictation) to 53 % (spontaneous conversation) depending on the speaking style. These experiments show that speaking style is a dominant factor in determining the performance of large-vocabulary conversational speech recognition (LVCSR) systems. 1.

Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration, except where stated. It has not been submitted in whole or part for a degree at any other university. The length of this thesis including footnotes and appendices does not exceed 29,500 words and includes no more than 40 figures. 1 Systems which automatically transcribe carefully dictated speech are now commercially available, but their performance degrades dramatically when the speaking style of users becomes more relaxed or conversational. This dissertation focuses on techniques that aim to improve the robustness of statistical speech transcription systems to conversational speaking styles. The dissertation shows first that the performance degradation occuring as speech becomes more conversational is severe and is partially attributable to differences in the acoustic realizations of sentences. Hypothesizing that the quantifiably wider range of