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基于汉语语音音节特点的N-Best改进算法.docx

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基于汉语语音音节特点的N-Best改进算法 Title:AnImprovedN-BestAlgorithmBasedonChineseSpeechSyllableCharacteristics Abstract: Inrecentyears,automaticspeechrecognition(ASR)systemshavemadesignificantprogress,enhancingthecommunicationbetweenhumanandmachine.OnecrucialcomponentofASRisthelanguagemodel,whichplaysasignificantroleinconvertingspeechintotextaccurately.TheN-Bestalgorithmiswidelyusedinlanguagemodelingtogeneratealistofthemostprobablealternativewordsequences.Inthispaper,weproposeanimprovedN-BestalgorithmbasedontheuniquecharacteristicsofChinesespeechsyllables.ThealgorithmtakesadvantageofthespecificpropertiesofChinesesyllablestoenhancetheaccuracyandefficiencyoftheASRsystem. 1.Introduction AutomaticSpeechRecognition(ASR)hasbecomeanintegralpartofmanyapplications,suchasvoiceassistants,transcriptionservices,andlanguagelearningplatforms.TheperformanceofASRheavilyreliesonthelanguagemodel,whichpredictsthemostprobablewordsequencegiventheinputspeech.TheN-Bestalgorithmiscommonlyusedtogeneratealistofthemostlikelyalternativewordsequences,providingflexibilityinchoosingthebestoutput.However,duetothestructuralcomplexityofChinesecharactersandthedifferentrulesgoverningsyllables,theapplicationofN-BestalgorithminChineseASRneedstobeimproved.ThispaperaimstoproposeanoptimizedN-BestalgorithmbasedonthecharacteristicsofChinesespeechsyllables. 2.CharacteristicsofChineseSpeechSyllables Chineseisatonallanguagewithalargenumberofhomophones,andthesyllablesarecomposedofinitials(consonants),finals(vowels),andtones.ChinesespeechsyllablesexhibitseveraluniquecharacteristicsthatcanbeutilizedforN-Bestalgorithmimprovement: 2.1.ToneDependency: Chinesesyllablescontainfourdistincttones,whichsignificantlyimpactthemeaningoftheword.Therefore,therecognitionaccuracycanbeimprovedbyconsideringthetoneinformationintheN-Bestalgorithm. 2.2.ContextualInfluence: SyllablesinChineseoftenexhibitcontextualinfluence,wherethepronunciationandmeaningcanvarydependingonthesurroundingsyllables.Incorporatingthecontextualinformationcanenhancetheaccura