Voice activity detection using feature vectors

dc.contributor.author	Thati, Jagadeesh	en
dc.contributor.author	Noorbasha, Fazal	en
dc.date.accessioned	2015-02-02T09:53:06Z
dc.date.available	2015-02-02T09:53:06Z
dc.date.issued	2015-02-02
dc.identifier.uri	http://hdl.handle.net/11400/5441
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://e-jst.teiath.gr/	en
dc.subject	Voice activity
dc.subject	Φωνητική δραστηριότητα
dc.subject	Feature vectors
dc.subject	Διανύσματα χαρακτηριστικών γνωρισμάτων
dc.subject	k-means clustering
dc.title	Voice activity detection using feature vectors	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Electronics
heal.classification	Τεχνολογία
heal.classification	Ηλεκτρονική
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://zbw.eu/stw/descriptor/10455-2
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Ηλεκτρονική
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85095226
heal.language	en
heal.access	free
heal.publicationDate	2011
heal.bibliographicCitation	Thati, J. and Noorbasha, F. (2011). Voice activity detection using feature vectors. "e-Journal of Science & Technology". [Online] 6(4): 29-32. Available from: http://e-jst.teiath.gr/	en
heal.abstract	Effective speech communication can be achieved by taking the speech signal when microphone is active and suppressing the noise when it is passive. The model we proposed in this paper is to take Feature vectors of pre-defined speech and noise signal’s, which already are stored for processing. Then centriods of the Feature Vectors were calculated using k-means algorithm. The Minimum distance between framed feature vectors of input signal and centriods of pre-defined signals are estimated using Euclidian distance. The ratio obtained between noise and speech minimum distance vectors will represent the voice activity at the microphone. The evaluation of the ratio indicates the significant performance of voice activity detection in noisy environment as well.	en
heal.publisher	Νερατζής, Ηλίας	el
heal.publisher	Σιανούδης, Ιωάννης	el
heal.journalName	e-Journal of Science & Technology	en
heal.journalName	e-Περιοδικό Επιστήμης & Τεχνολογίας	el
heal.journalType	peer-reviewed
heal.fullTextAvailability	true