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ID:40714150
大小:2.17 MB
页数:48页
时间:2019-08-06
《Deep Learning in Speech Synthesis by Google 2013》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、DeepLearninginSpeechSynthesisHeigaZenGoogleAugust31st,2013OutlineBackgroundDeepLearningDeepLearninginSpeechSynthesisMotivationDeeplearning-basedapproachesDNN-basedstatisticalparametricspeechsynthesisExperimentsConclusionText-to-speechassequence-to-sequencemap
2、pingAutomaticspeechrecognition(ASR)Speech(continuoustimeseries)!Text(discretesymbolsequence)Machinetranslation(MT)Text(discretesymbolsequence)!Text(discretesymbolsequence)Text-to-speechsynthesis(TTS)Text(discretesymbolsequence)!Speech(continuoustimeseries)
3、HeigaZenDeepLearninginSpeechSynthesisAugust31st,20131of50Speechproductionprocesstext(concept)fundamentalreqvoiced/unoicedfreqtransercharfrequencyspeechtransfercharacteristicsmagnitudestart--endSoundsourcefundamentalvoiced:pulsefrequencyunvoiced:noisemodulatio
4、nofcarierwavebyspechinformationairflowHeigaZenDeepLearninginSpeechSynthesisAugust31st,20132of50Typical owofTTSsystemTEXTSentencesegmentaitonWordsegmentationTextnormalizationTextanalysisPart-of-speechtaggingPronunciationProsodypredictionSpeechsynthesisdiscrete
5、⇒discreteWaveformgenerationNLPFrontendSYNTHESIZEDdiscrete⇒continuousSPEECHSpeechBackendThistalkfocusesonbackendHeigaZenDeepLearninginSpeechSynthesisAugust31st,20133of50Statisticalparametricspeechsynthesis(SPSS)[2]FeatureModelParameterWaveformSynthesizedSpeech
6、extractiontraininggenerationsynthesisSpeechTextTextLargedata+automatictraining!AutomaticvoicebuildingParametricrepresentationofspeech!FlexibletochangeitsvoicecharacteristicsHiddenMarkovmodel(HMM)asitsacousticmodel!HMM-basedspeechsynthesissystem(HTS)[1]Heiga
7、ZenDeepLearninginSpeechSynthesisAugust31st,20134of50CharacteristicsofSPSSAdvantages Flexibilitytochangevoicecharacteristics Smallfootprint RobustnessDrawback QualityMajorfactorsforqualitydegradation[2] Vocoder Acousticmodel!Deeplearning OversmoothingHeigaZ
8、enDeepLearninginSpeechSynthesisAugust31st,20135of50Deeplearning[3]Machinelearningmethodologyusingmultiple-layeredmodelsMotivatedbybrains,whichorganizeideasandconceptshierarchicallyTypi
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