Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/8940
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dc.contributor.authorRamteke, P.B.
dc.contributor.authorKoolagudi, S.G.
dc.contributor.authorAfroz, F.
dc.date.accessioned2020-03-30T10:23:05Z-
dc.date.available2020-03-30T10:23:05Z-
dc.date.issued2016
dc.identifier.citationSmart Innovation, Systems and Technologies, 2016, Vol.43, , pp.611-617en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8940-
dc.description.abstractThis paper mainly focuses on detection of repetitions in stuttered speech. The stuttered speech signal is divided into isolated units based on energy. Mel-frequency cepstrum coefficients (MFCCs), formants and shimmer are used as features for repetition recognition. These features are extracted from each isolated unit. Using Dynamic Time Warping (DTW) the features of each isolated unit are compared with those subsequent units within one second interval of speech. Based on the analysis of scores obtained from DTW a threshold is set, if the score is below the set threshold then the units are identified as repeated events. Twenty seven seconds of speech data used in this work, consists of 50 repetition events. The result shows that the combination of MFCCs, formants and shimmer can be used for the recognition of repetitions in stuttered speech. Out of 50 repetitions, 47 are correctly identified. � Springer India 2016.en_US
dc.titleRepetition detection in stuttered speechen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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