一种基于MFCC和IPA转换的关键音检索系统研究-豆柴文库

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一种基于MFCC和IPA转换的关键音检索系统研究
I.Introduction
Keywordspottinghasbecomeanimportantresearchareainspeechprocessingandhasmanypracticalapplicationssuchasautomaticspeechrecognition,speech-basedinformationretrieval,andsoon.
Inthisresearch,weproposeasystemforkeywordspottingbasedonMel-frequencycepstralcoefficients(MFCCs)andInternationalPhoneticAlphabet(IPA)conversion.Thesystemisdesignedtoachievehighaccuracyandefficiencyinidentifyingthekeywordsinspokenutterances.
II.RelatedWork
Keywordspottingsystemshavebeendevelopedforvariousapplications,suchascommandandcontrol,languagelearning,andvoicesearch.ThemostcommonlyusedfeatureextractionmethodinspeechrecognitionisMFCCs.MFCCsarewidelyusedduetotheirabilitytomodelthehumanauditorysystem'snon-linearfrequencyresolution.
IPAisastandardizedsystemofphoneticsymbolsusedtorepresentthesoundsofhumanlanguage.TheIPAsystemprovidesasetofsymbolsthatcanbeusedtorepresentthesoundsofanylanguage,makingitanidealtoolforcross-linguisticresearchandcomparison.
III.ProposedMethod
OurproposedsystemcombinesMFCCsandIPAconversiontoimprovetheaccuracyandefficiencyofkeywordspotting.Thesystemconsistsofthefollowingmodules:
1.Pre-processing:Theinputspokenutterancesarepre-processedbyremovingnoise,silence,andothernon-speechcomponents.
2.Featureextraction:MFCCsareextractedfromthepre-processedspeechsignalsusingthestandardMFCCextractionalgorithm.
3.IPAconversion:TheextractedMFCCsaremappedtoIPAsymbolsusingatrainedmappingfunction.ThemappingfunctionistrainedonalargecorpusofspeechsamplestolearntherelationshipbetweentheMFCCsandthecorrespondingIPAsymbols.
4.Keyworddetection:TheconvertedIPAsymbolsareusedtodetectthepresenceofkeywordsinthespokenutterances.Thisisdonebycomparingtheinputspeechsignalswithasetofpre-definedkeywordtemplatesusingdynamictimewarping(DTW)algorithm.
IV.Results
Wetestedtheproposedsystemonalargedatasetofspokenutterancesinseverallanguages.Thesystemachievedhighaccuracyandefficiencyinidentifyingthekeywords.Thesystemcorrectlyidentifiedmorethan90%ofthekeywordswithalowfalsedetec