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基于AMR的语音质量提升方法研究.docx

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基于AMR的语音质量提升方法研究 Abstract AutomaticSpeechRecognition(ASR)systemsarewidelyusedinvariousfieldssuchashealthcare,education,andfinance.ThequalityofASRoutputdependsonthequalityoftheaudioinput,whichmaybeaffectedbyvariousfactorssuchasnoise,codingartifacts,andchannelcharacteristics.Inthispaper,weproposeamethodtoimprovethequalityofAMR-encodedspeechusingvarioustechniquesincludingnoisereduction,de-artifacting,andchannelequalization.ExperimentalresultsshowthattheproposedmethodcansignificantlyimprovethespeechrecognitionaccuracyofAMR-encodedspeech. Introduction Speechrecognitionhasbecomeanessentialtechnologyinmodernsociety.However,thequalityofthespeechrecognitionsystemdependsonthequalityoftheinputspeech.Theacousticenvironmentmayintroducevariousnoises,distortions,andartifactsthatcandegradethequalityofspeechsignals,resultinginlowrecognitionaccuracy.Moreover,speechsignalsareusuallycompressedtoreducestorageandtransmissionoverheads.However,thecompressionprocesscanintroduceevenmoredistortionandcodingartifacts. AdaptiveMulti-Rate(AMR)isawidelyusedspeechcodingstandardthatcanprovidedecentspeechqualityatlowbitrates.AMRisusedinvariousapplicationssuchasmobilecommunication,videoconferencing,andvoicemessaging.However,AMR-encodedspeechsignalsaresusceptibletovariousdistortionssuchaschannelfading,noise,andcodingartifacts.Therefore,enhancingthespeechqualityofAMR-encodedspeechisessentialtoimprovetheperformanceofspeechrecognitionsystems. Inthispaper,weproposeamethodtoimprovethequalityofAMR-encodedspeechusingvarioustechniquesincludingnoisereduction,de-artifacting,andchannelequalization.TheproposedmethodcanbeusedtoenhancetheperformanceofbothspeechrecognitionandspeakerverificationsystemsthatoperateonAMR-encodedspeechsignals. Relatedwork Varioustechniqueshavebeenproposedtoimprovethequalityofspeechsignals.Forexample,noisereductiontechniquescanremovetheadditivenoisefromspeechsignals,thusimprovingtheperceptualqualityofspeech.De-artifactingtechniquescanremovethecodingartifactsintroducedbycompressionandtransm