Advances in statistical estimation and tracking of AM-FM speech components

Katsamanis, A; Maragos, P

dc.contributor.author	Katsamanis, A	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:43:06Z
dc.date.available	2014-03-01T02:43:06Z
dc.date.issued	2005	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31229
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-33745196020&partnerID=40&md5=5da0a93c02d63f815d5f1bc137536162	en
dc.relation.uri	http://cvsp.cs.ntua.gr/projects/pub/HIWIRE/HiwirePublications/KatsamanisMaragos_StatisticalTracking_IS2005.pdf	en
dc.relation.uri	http://www.isca-speech.org/archive/interspeech_2005/i05_1125.html	en
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/conf/interspeech/interspeech2005.html#KatsamanisM05	en
dc.subject	Bandpass Filter	en
dc.subject	Frequency Estimation	en
dc.subject	Particle Filter	en
dc.subject	Statistical Estimation	en
dc.subject.other	Algorithms	en
dc.subject.other	Bandpass filters	en
dc.subject.other	Natural frequencies	en
dc.subject.other	Resonance	en
dc.subject.other	Speech analysis	en
dc.subject.other	Statistical methods	en
dc.subject.other	AM-FM speech components	en
dc.subject.other	Particle filtering	en
dc.subject.other	Real speech signals	en
dc.subject.other	Statistical estimation	en
dc.subject.other	Acoustic signal processing	en
dc.title	Advances in statistical estimation and tracking of AM-FM speech components	en
heal.type	conferenceItem	en
heal.publicationDate	2005	en
heal.abstract	In this paper we present two extensions of a statistical framework to demodulate speech resonances, which are modeled as AM-FM signals. The first approach utilizes bandpass filtering and a standard demodulation algorithm which regularizes instantaneous amplitude and frequency estimates. The second employs particle filtering techniques to allow temporal variations of the parameters that are connected with spectral characteristics of the analyzed signal. Results are presented on both synthetic and real speech signals and improved performance is demonstrated. Both approaches appear to cope quite satisfactorily with the nonstationarity of speech signals.	en
heal.journalName	9th European Conference on Speech Communication and Technology	en
dc.identifier.spage	1125	en
dc.identifier.epage	1128	en