Adaptive detection of noisy speech using third-order statistics

Rangoussi, M; Carayannis, G

dc.contributor.author	Rangoussi, M	en
dc.contributor.author	Carayannis, G	en
dc.date.accessioned	2014-03-01T01:11:39Z
dc.date.available	2014-03-01T01:11:39Z
dc.date.issued	1996	en
dc.identifier.issn	0890-6327	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11761
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-3743097049&partnerID=40&md5=96af6297b7661fcb48451e074c945a40	en
dc.subject	Adaptive	en
dc.subject	Detection	en
dc.subject	Speech	en
dc.subject	Third-order cumulants	en
dc.subject.classification	Automation & Control Systems	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Adaptive control systems	en
dc.subject.other	Algorithms	en
dc.subject.other	Detectors	en
dc.subject.other	Feedback	en
dc.subject.other	Performance	en
dc.subject.other	Signal detection	en
dc.subject.other	Signal to noise ratio	en
dc.subject.other	Speech	en
dc.subject.other	Spurious signal noise	en
dc.subject.other	Statistical methods	en
dc.subject.other	Additive noises	en
dc.subject.other	Decision feedback	en
dc.subject.other	Gaussianity test	en
dc.subject.other	Noisy speech	en
dc.subject.other	Speech detection	en
dc.subject.other	Speech intervals	en
dc.subject.other	Third order cumulants	en
dc.subject.other	Speech processing	en
dc.title	Adaptive detection of noisy speech using third-order statistics	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	1996	en
heal.abstract	Detection of speech in noisy recordings is challenging, especially when the noise does not follow the usual whiteness, stationarity and high signal-to-noise ratio assumptions. A robust speech detector can affect significantly the performance of several speech-processing tasks, such as endpoint detection, segmentation and finally recognition, if we deal with real life data as opposed to laboratory or controlled environment recordings. The detector proposed in this paper is based on a Gaussianity test that employs third-order cumulants of the data to decide on the binary hypotheses of noise only versus speech plus noise. Speech intervals are detected by exploiting the third-order information present in the speech signal. The detector can tolerate a large family of additive noises thanks to its third-order statistics basis. The sample-adaptive and decision feedback variations proposed here provide the detector with tracking ability with respect to both the time variations of speech and the possible non-stationarity of noise. Experiments carried out using real data recorded in a moving car interior show satisfactory performance of the proposed algorithms down to - 6 dB signal-to-noise ratio.	en
heal.publisher	JOHN WILEY & SONS LTD	en
heal.journalName	International Journal of Adaptive Control and Signal Processing	en
dc.identifier.isi	ISI:A1996UD00700003	en
dc.identifier.volume	10	en
dc.identifier.issue	2	en
dc.identifier.spage	113	en
dc.identifier.epage	136	en