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14 septembre 2014
- handle: 10670/1.6a7gnc
- hal: hal-01134812
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Camille Dutrey et al., « A CRF-Based Approach to Automatic Disfluency Detection in a French Call-Centre Corpus », HAL-SHS : linguistique, ID : 10670/1.6a7gnc
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In this paper, we present a Conditional Random Field based approach for automatic detection of edit disfluencies in a conversational telephone corpus in French. We define disfluency patterns using both linguistic and acoustic features to perform disfluency detection. Two related tasks are considered: the first task aims at detecting the disfluent speech portion proper or reparandum, i.e. the portion to be removed if we want to improve the readability of transcribed data ; in the second task, we aim at identifying also the corrected portion or repair which can be useful in follow-up discourse and dialogue analyses or in opinion mining. For these two tasks, we present comparative results as a function of the involved type of features (acoustic and/or linguistic). Generally speaking, best results are obtained by CRF models combining both acoustic and linguistic features.