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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Repetition Detection in Stuttered Speech
verfasst von : Pravin B. Ramteke, Shashidhar G. Koolagudi, Fathima Afroz
Erschienen in: Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics
Verlag: Springer India
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Abstract
This 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.