Depitch and the role of fundamental frequency in speaker recognition
Pitch information is known to be partially conveyed in Mel cepstral features that are commonly used for speaker recognition. In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the...
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description | Pitch information is known to be partially conveyed in Mel cepstral features that are commonly used for speaker recognition. In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the fundamental frequency was shown to degrade speaker recognition performance. This paper introduces a signal processing procedure termed depitch that attempts to remove pitch information from the speech signal. Recognition experiments carried out on the female subset of the NIST 2002 Speaker Recognition Evaluation show that by combining scores from a conventional and a depitched system, a substantial improvement in equal error rate is obtained for high pitched speakers and pitch-mismatched trials. Performing pitch/depitch score fusion is also shown to help alleviate the well-known problem of "goat" speakers. |
doi_str_mv | 10.1109/ICASSP.2003.1202299 |
format | Conference Proceeding |
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In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the fundamental frequency was shown to degrade speaker recognition performance. This paper introduces a signal processing procedure termed depitch that attempts to remove pitch information from the speech signal. Recognition experiments carried out on the female subset of the NIST 2002 Speaker Recognition Evaluation show that by combining scores from a conventional and a depitched system, a substantial improvement in equal error rate is obtained for high pitched speakers and pitch-mismatched trials. Performing pitch/depitch score fusion is also shown to help alleviate the well-known problem of "goat" speakers.</description><identifier>ISSN: 1520-6149</identifier><identifier>ISBN: 9780780376632</identifier><identifier>ISBN: 0780376633</identifier><identifier>EISSN: 2379-190X</identifier><identifier>DOI: 10.1109/ICASSP.2003.1202299</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cepstral analysis ; Degradation ; Error analysis ; Mel frequency cepstral coefficient ; Power harmonic filters ; Power system harmonics ; Signal processing ; Speaker recognition ; Speech processing ; Testing</subject><ispartof>2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. 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(ICASSP '03)</title><addtitle>ICASSP</addtitle><description>Pitch information is known to be partially conveyed in Mel cepstral features that are commonly used for speaker recognition. In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the fundamental frequency was shown to degrade speaker recognition performance. This paper introduces a signal processing procedure termed depitch that attempts to remove pitch information from the speech signal. Recognition experiments carried out on the female subset of the NIST 2002 Speaker Recognition Evaluation show that by combining scores from a conventional and a depitched system, a substantial improvement in equal error rate is obtained for high pitched speakers and pitch-mismatched trials. Performing pitch/depitch score fusion is also shown to help alleviate the well-known problem of "goat" speakers.</description><subject>Cepstral analysis</subject><subject>Degradation</subject><subject>Error analysis</subject><subject>Mel frequency cepstral coefficient</subject><subject>Power harmonic filters</subject><subject>Power system harmonics</subject><subject>Signal processing</subject><subject>Speaker recognition</subject><subject>Speech processing</subject><subject>Testing</subject><issn>1520-6149</issn><issn>2379-190X</issn><isbn>9780780376632</isbn><isbn>0780376633</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jjkOwjAQAFccEuF4Ac1-IGFtQxKXiEPQIUFBh6ywAUNwghMKfg8FNdJIU0wzAGNBkRCkJ9vFfL_fRZJIRUKSlFq3IJAq0aHQdGzDSCcpfVFJHCvZgUDMJIWxmOoe9Ov6RkRpMk0DWC65sk12RePO2FwZfVkwljnmL3c2D3aNKTD3_Hyxy95oHdYVmzt79JyVF2cbW7ohdHNT1Dz6eQDj9eqw2ISWmU-Vtw_j36ffqPpfP5Q_PuI</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Zilea, R.D.</creator><creator>Navratil, J.</creator><creator>Ramaswamy, G.N.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2003</creationdate><title>Depitch and the role of fundamental frequency in speaker recognition</title><author>Zilea, R.D. ; Navratil, J. ; Ramaswamy, G.N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_12022993</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Cepstral analysis</topic><topic>Degradation</topic><topic>Error analysis</topic><topic>Mel frequency cepstral coefficient</topic><topic>Power harmonic filters</topic><topic>Power system harmonics</topic><topic>Signal processing</topic><topic>Speaker recognition</topic><topic>Speech processing</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Zilea, R.D.</creatorcontrib><creatorcontrib>Navratil, J.</creatorcontrib><creatorcontrib>Ramaswamy, G.N.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zilea, R.D.</au><au>Navratil, J.</au><au>Ramaswamy, G.N.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Depitch and the role of fundamental frequency in speaker recognition</atitle><btitle>2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)</btitle><stitle>ICASSP</stitle><date>2003</date><risdate>2003</risdate><volume>2</volume><spage>II</spage><epage>81</epage><pages>II-81</pages><issn>1520-6149</issn><eissn>2379-190X</eissn><isbn>9780780376632</isbn><isbn>0780376633</isbn><abstract>Pitch information is known to be partially conveyed in Mel cepstral features that are commonly used for speaker recognition. In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the fundamental frequency was shown to degrade speaker recognition performance. This paper introduces a signal processing procedure termed depitch that attempts to remove pitch information from the speech signal. Recognition experiments carried out on the female subset of the NIST 2002 Speaker Recognition Evaluation show that by combining scores from a conventional and a depitched system, a substantial improvement in equal error rate is obtained for high pitched speakers and pitch-mismatched trials. Performing pitch/depitch score fusion is also shown to help alleviate the well-known problem of "goat" speakers.</abstract><pub>IEEE</pub><doi>10.1109/ICASSP.2003.1202299</doi></addata></record> |
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identifier | ISSN: 1520-6149 |
ispartof | 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03), 2003, Vol.2, p.II-81 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Cepstral analysis Degradation Error analysis Mel frequency cepstral coefficient Power harmonic filters Power system harmonics Signal processing Speaker recognition Speech processing Testing |
title | Depitch and the role of fundamental frequency in speaker recognition |
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