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dc.contributor.authorNayak, J.-
dc.contributor.authorBhat, P.S.-
dc.date.accessioned2020-03-30T10:18:15Z-
dc.date.available2020-03-30T10:18:15Z-
dc.date.issued2003-
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2003, Vol.2, , pp.951-953en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8231-
dc.description.abstractThis paper attempts to identify pathological disorders of larynx using Wavelet Analysis. Speech samples carry symptoms of disorder in the place of their origin. The speech signal is subjected to wavelet analysis, and the coefficients are used to identify disorders such as Vocal Fold Paralysis. Multilayer Artificial Neural Network is used for classification of normal and affected signals.en_US
dc.titleIdentification of voice disorders using speech samplesen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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