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Analysis of in-car speech recognition experiments using a large-scale multi-mode dialogue corpus

The dependency of conversational utterances on themode of dialogue is analyzed. A speech corpus of 800 speakers collected under three different modes, i.e., talking to a human operator, an WOZ system and an ASR system, is used for analysis. Some characteristics such as sentence complexity loudness of the voice and speaking-rate are found to be significantly different among the dialogue modes. Linear regression analysis results also clarify the relative importance of those characteristics on speech recognition accuracy.