Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/7879
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dc.contributor.authorRamteke, P.B.
dc.contributor.authorSadanand, A.
dc.contributor.authorKoolagudi, S.G.
dc.contributor.authorPai, V.
dc.date.accessioned2020-03-30T10:02:59Z-
dc.date.available2020-03-30T10:02:59Z-
dc.date.issued2017
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, Vol.2017-December, , pp.2840-2845en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7879-
dc.description.abstractIn this work, consonant aspiration and unaspiration phenomena are studied. It is known that, pronunciation of aspiration and unaspiration is characterized by the 'puff of air' released at the place of constriction in the vocal tract which is known as burst. Here, the properties of vowel immediately after the burst are studied for characterization of the burst. Excitation source signal estimated from the speech linear prediction residual is used for the task. The signal characteristics such as glottal pulse, duration of open, closed & return phases, slope of open & return phases, duration of burst, ratio of highest and lowest energies of signal and voice onset time (VOT) are explored to characterize aspiration and unaspiration. TIMIT English speech corpus is used to test the proposed approach. Random forest (RF) and support vector machine (SVMs) are used as classifiers to test the effectiveness of the features used for the task. An accuracy of 99.93% and 94.03% is achieved respectively. From the results, it is observed that the proposed features are robust in classifying the aspirated and unaspirated consonants. � 2017 IEEE.en_US
dc.titleCharacterization of aspirated and unaspirated sounds in speechen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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