Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/34169
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dc.coverage.spatialText independent speaker Identification system using fused mel Frequency feature sets based on Gaussian mixture modelen_US
dc.date.accessioned2015-02-10T06:59:01Z-
dc.date.available2015-02-10T06:59:01Z-
dc.date.issued2015-02-10-
dc.identifier.urihttp://hdl.handle.net/10603/34169-
dc.description.abstractSpeaker identification is the process of identifying the individual newlineusing the individual s speech signal for applications like secure information newlineaccess system voice based attendance entry system, forensic system etc newlineConventional speaker identification systems use long duration speech signals newlinefor identifying the speaker The difficulty with speaker identification using newlineshort duration speech signal is in acquiring sufficient speaker specific newlineinformation from the speech signal This thesis investigates five methods of newlinespeaker identification by utilizing short utterance of speech signals Block newlinetruncation on wavelet sub band processed speech signal cross lingual speech newlineprocessing multilingual speech processing combined vocal tract and auditory newlinesystems quadrilateral structure filter bank analysis are used to obtain efficient newlineclosed set text independent speaker identification newlineA narrow band noise robust speaker identification system presented newlinein this thesis is based on the idea of using sub band processing followed by newlineblock truncation to build the model of a particular speaker When a speech newlinesignal is partly degraded by a narrow band frequency selective noise a part newlineof the speech spectrum may still be uncorrupted This uncorrupted spectrum newlineprovides an opportunity for improvement in speaker identification newlineperformance if the speech signal is processed in sub bands newline newlineen_US
dc.format.extentxx, 151p.en_US
dc.languageEnglishen_US
dc.relationp136-150.en_US
dc.rightsuniversityen_US
dc.titleText independent speaker Identification system using fused mel Frequency feature sets based on Gaussian mixture modelen_US
dc.title.alternativeen_US
dc.creator.researcherSelva nidhyananthan Sen_US
dc.subject.keywordQuadrilateral structure filter banken_US
dc.subject.keywordspeech signal is processeden_US
dc.description.noterefernce p136-150.en_US
dc.contributor.guideShantha selva kumara Ren_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/10/2014en_US
dc.date.awarded30/10/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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02_cetrificate.pdf149.56 kBAdobe PDFView/Open
03_abstract.pdf20.66 kBAdobe PDFView/Open
04_acknowledgement.pdf16.69 kBAdobe PDFView/Open
05_content.pdf74.8 kBAdobe PDFView/Open
06_chapter1.pdf116.81 kBAdobe PDFView/Open
07_chapter2.pdf68.52 kBAdobe PDFView/Open
08_chapter3.pdf159.22 kBAdobe PDFView/Open
09_chapter4.pdf114.49 kBAdobe PDFView/Open
10_chapter5.pdf226.01 kBAdobe PDFView/Open
11_chapter6.pdf2.29 MBAdobe PDFView/Open
12_chapter7.pdf96.34 kBAdobe PDFView/Open
13_chapter8.pdf1.74 MBAdobe PDFView/Open
14_chapter9.pdf34.19 kBAdobe PDFView/Open
15_reference.pdf87.5 kBAdobe PDFView/Open
16_publication.pdf28.87 kBAdobe PDFView/Open


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