Rebecca A. Bates

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We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speechact-like units such as STATEMENT,QUESTION, BACKCHANNEL,AGREEMENT, DISAGREEMENT, and APOLOGY. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence.(More)
Identifying whether an utterance is a statement, question, greeting, and so forth is integral to effective automatic understanding of natural dialog. Little is known, however, about how such dialog acts (DAs) can be automatically classified in truly natural conversation. This study asks whether current approaches, which use mainly word information, could be(More)
We describe a statistical approach for modeling dialog acts in conversational speech, i.e., speechact-like units such as Statement, Question, Backchannel, Agreement, Disagreement, and Apology. Our model detects and predicts dialog acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialog act sequence. The(More)
We study the problem of detecting linguistic events at interword boundaries, such as sentence boundaries and disfluency locations, in speech transcribed by an automatic recognizer. Recovering such events is crucial to facilitate speech understanding and other natural language processing tasks. Our approach is based on a combination of prosodic cues modeled(More)
We describe a new approach for statistical modeling and detection of discourse structure for natural conversational speech. Our model is based on 42 ‘Dialog Acts’ (DAs), (question, answer, backchannel, agreement, disagreement, apology, etc). We labeled 1155 conversations from the Switchboard (SWBD) database (Godfrey et al. 1992) of human-to-human telephone(More)
Speech disfluencies (filled pauses, repetitions, repairs, and false starts) are pervasive in spontaneous speech. The ability to detect and correct disfluencies automatically is important for effective natural language understanding, as well as to improve speech models in general. Previous approaches to disfluency detection have relied heavily on lexical(More)
A significant source of variation in spontaneous speech is due to intra-speaker pronunciation changes. Previous work in automatic speech recognition has identified several factors that affect pronunciation variability such as phonetic context and speaking rate, as well as syntactic structure. This work examines prosody as a cue to pronunciation variability,(More)
We describe a new system for labeling speech corpora with high-level group interaction tags, called “meeting acts.” The system was motivated by a need to assess work seeking to automatically detect meeting style using dialog act information. We present information about the relationships seen between dialog act sequences and meeting style to motivate the(More)
A significant source of variation in spontaneous speech is due to intra-speaker pronunciation changes. Previous work in automatic speech recognition has identified several factors that affect pronunciation variability such as phonetic context and speaking rate. This work examines new higher level information sources: syntax and discourse structure,(More)
The antiorthostatic suspension model simulates certain physiological effects of spaceflight. We have previously reported BDF1 mice suspended by the tail in the antiorthostatic orientation for 4 days express high levels of resistance to virulent Listeria monocytogenesinfection. In the present study, we examined whether the increased resistance to this(More)