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

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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 http://hdl.handle.net/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

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