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dc.contributor.advisorSvendsen, Torbjørnnb_NO
dc.contributor.authorHamar, Jarle Baucknb_NO
dc.date.accessioned2014-12-19T13:44:22Z
dc.date.accessioned2015-12-22T11:42:18Z
dc.date.available2014-12-19T13:44:22Z
dc.date.available2015-12-22T11:42:18Z
dc.date.created2010-09-04nb_NO
dc.date.issued2009nb_NO
dc.identifier348877nb_NO
dc.identifierntnudaim:4845
dc.identifier.urihttp://hdl.handle.net/11250/2369463
dc.description.abstractThis work explores an alternative set of features to the frequently used melfrequency coefficients (MFCCs). The cochlea features simulate the nerve fibre signal sent from the ear to the brain. In this study the usage of the cochlea features for acoustic segmentation is of main interest. Both the cochlea features and a variant of combining them with zero crossing with peak amplitude (ZCPA) have been used as input to an acoustic segmentation algorithm. Also experiments using the cochlea features as input to an artificial neural network (ANN) for classifying each vector as boundary/non-boundary have been performed. The results show that the features contain a great deal of information regarding the speech signal. Especially the combination of cochlea and ZCPA are giving good results.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for elektronikk og telekommunikasjonnb_NO
dc.subjectntnudaimno_NO
dc.subjectSIE7 kommunikasjonsteknologi
dc.subjectSignalbehandling og kommunikasjon
dc.titleCochlear Features for Acoustic Segmentationnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber62nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for elektronikk og telekommunikasjonnb_NO


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