Using information above the word level for automatic speech recognition
This thesis introduces a general method for using information at the utterance level and across utterances for automatic speech recognition. The method involves classification of utterances into types. Using constraints at the utterance level via this classification method allows information sources to be exploited which cannot necessarily be used directly for word recognition. The classification power of three sources of information is investigated: the language model in the speech recogniser, dialogue context and intonation. The method is applied to a challenging task: the recognition of spontaneous dialogue speech. The results show success in automatic utterance type classification, and subsequent word error rate reduction over a baseline system, when all three information sources are probabilistically combined.
King, Simon Alistair
automatic speech recognition
Using information above the word level for automatic speech recognition. This thesis introduces a general method for using information at the utterance level and across utterances for automatic speech recognition. The method involves classification of utterances into types. Using constraints at the utterance level via this classification method allows information sources to be exploited which cannot necessarily be used directly for word recognition. The classification power of three sources of information is investigated: the language model in the speech recogniser, dialogue context and intonation. The method is applied to a challenging task: the recognition of spontaneous dialogue speech. The results show success in automatic utterance type classification, and subsequent word error rate reduction over a baseline system, when all three information sources are probabilistically combined.
using information word level automatic_speech recognition introduces general method_use information utterance level across utterance automatic_speech recognition method_involve classification utterance type using constraint utterance level via classification method_allow information source exploit necessarily use directly word_recognition classification power source_information investigate language model speech recogniser dialogue context intonation method_apply challenge task recognition spontaneous dialogue speech show success automatic utterance type classification subsequent word error rate reduction baseline system information source combine