简介：Auditorymodelhasbeenappliedtoseveralaspectsofspeechsignalprocessingfield,andappearstobeeffectiveinperformance.Thispaperpresentstheinversetransformofeachstageofonewidelyusedauditorymodel.Firstofallitisnecessarytoinvertcorrelogramandreconstructphaseinformationbyrepetitiousiterationsinordertogetauditory-nervefiringrate.ThenextstepistoobtainthenegativepartsofthesignalviathereverseprocessoftheHWR(HalfWaveRectification).Finallythefunctionsofinnerhaircell/synapsemodelandGammatonefiltershavetobeinverted.Thusthewholeauditorymodelinversionhasbeenachieved.Anapplicationofnoisyspeechenhancementbasedonauditorymodelinversionalgorithmisproposed.Manyexperimentsshowthatthismethodiseffectiveinreducingnoise.EspeciallywhenSNRofnoisyspeechislowitismoreeffectivethanothermethods.Thusthisauditorymodelinversionmethodgiveninthispaperisapplicabletospeechenhancementfield.

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简介：Inordertoprovidethebasisforparameterselectionofvocaldiseasesclassification,anonlineardynamicmodelingmethodisproposed.Abiomechanicalmodelofvocalcordswithpolyporparalysis,whichcouplestoglottalairflowtoproducelaryngealsoundsource,isintroduced.Andthenthefundamentalfrequencyanditsperturbationparametersaresolved.Poincaresectionandbifurcationdiagramareappliedtononlinearanalysisofmodelvibration.Bychangingthepathologicalparametersorsubglottalpressure,thechangesoffundamentalfrequencyandLyapunovexponentsareanalyzed.Thesimulationresultsshowthat,vocalcordparalysisreducesthefundamentalfrequency,andthechaosoccursonlywithinacertainpressurerange;whilevocalcordwithapolypdon’treducethefundamentalfrequency,chaosdistributesthroughouttheentirerangeofpressure.Thereforethisstudyishelpfulforclassificationofpolypandparalysisbytheacousticdiagnoses.

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简介：Arrayprocessingistoprocessthesignalscarriedbythepropagatingwavesreceivedatanarrayofsensors.Whenthesignalspropagatethroughthepracticalrandomtime-variantmedium,theirwavefrontscanshowtheprogres-sivelossesofcoherencewithincreasingspatialseparation.Thesedecorrelationsofwavefrontsresultinanangularspreadinthewavenumberspectrumcenteredaboutthetruesignaldircction-of-arrival.Thispaperputstheemphasisuponthearrayprocessingoftheangular-spreadsignalwhichiscalledtheGeneral-izedDirectional(GD)signalandaimstomatcharrayprocessingtothissignalmodelintheenergysense.Inthispaper,wealsopresentamethodofthecom-putersimulationorthegeneralizeddirectionalsignalmodel.Someresultsofcomputersimulationexperimentsandlake-tcstsinXinanjiangRiveraregiven.

简介：一个修改Parzen窗户方法，在低频率使分辨率高并且把光滑放在高频率，被建议获得统计模型。然后，当长句子被处理时，利用统计模型的一个性分类方法被建议，它有性分类的98%精确性。由男声音和女性表示的分离，与不同情感训练样品的讲话的平均数和标准差被用来创造相应情感模型。然后在测试样品和沥青的统计模型之间的Bhattacharyya距离，在沥青的speech.The正规化为情感识别被利用因为男声音和女声音也被考虑，以便说明他们直到一个一致空格。最后，讲话情感识别实验基于K最近的邻居显示出那，81%的正确的率被完成，在它仅仅是73.85%if的地方，传统的参数被利用。

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简介：Aspeechsignalprocessingandfeaturesextractingmethodbasedoncomputationalauditorymodelisproposed.Thecomputationalmodelisbasedonpsychological,physiologicalknowledgeanddigitalsignalprocessingmethods.Ineachstageofahearingperceptionsystem,thereisacorrespondingcomputationalmodeltosimulateitsfunction.Basedonthismodel,speechfeaturesareextracted.Ineachstage,thefeaturesindifferentkindsoflevelareextracted.Afurtherprocessingforprimaryauditoryspectrumbasedonlateralinhibitionisproposedtoextractmuchmorerobustspeechfeatures.Allthesefeaturescanberegardedastheinternalrepresentationsofspeechstimulationinhearingsystem.Therobustspeechrecognitionexperimentsareconductedtotesttherobustnessofthefeatures.Resultsshowthattherepresentationsbasedontheproposedcomputationalauditorymodelarerobustrepresentationsforspeechsignals.

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简介：AnewmethodologyofvoiceconversionincepstrumeigenspacebasedonstructuredGaussianmixturemodelisproposedfornon-parallelcorporawithoutjointtraining.Foreachspeaker,thecepstrumfeaturesofspeechareextracted,andmappedtotheeigenspacewhichisformedbyeigenvectorsofitsscattermatrix,therebytheStructuredGaussianMixtureModelintheEigenSpace(SGMM-ES)istrained.Thesourceandtargetspeaker’sSGMM-ESarematchedbasedonAcousticUniversalStructure(AUS)principletoachievespectrumtransformfunction.Experimentalresultsshowthespeakeridentificationrateofconversionspeechachieves95.25%,andthevalueofaveragecepstrumdistortionis1.25whichis0.8%and7.3%higherthantheperformanceofSGMMmethodrespectively.ABXandMOSevaluationsindicatetheconversionperformanceisquiteclosetothetraditionalmethodundertheparallelcorporacondition.TheresultsshowtheeigenspacebasedstructuredGaussianmixturemodelforvoiceconversionunderthenon-parallelcorporaiseffective.

简介：Acoupled-modesoundpropagationmodelwithcomplexeffectivedepthispresented,inordertoinvolvetheeffectofbranchlineintegralforacousticfieldinarange-dependentwaveguide.Theequationsofmotionandcontinuityareusedtoobtainthecoupledequations,whichsatisfyboundaryconditionsinthewaveguidewithvaryingtopographyandcontainonecouplingmatrix.Meanwhile,thecouplingsbetweendiscreteandcontinuousspectrumaredealtwithbasedoncomplexeffectivedepththeory.Numericalsimulationsshowthattheaccuracyoftransmissionlossisimprovedbythecoupledmodemodelwheneigenvaluesoftrappedmodesarelocatednearthebranchpoint.Theacousticfieldinanon-horizontallystratifiedwaveguidecanbecalculatedefficientlyandaccuratelybythismodel,andtheenergycorrespondingtotrappedmodes,leakymodesandbranchlineintegralcanbeconsideredadequately.

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简介：基于数字听觉的信号的批评乐队小浪变换嵌入算法的水位标在这份报纸被建议。为每个听觉的信号片断的掩盖的阀值被计算在上psychoacoustic基本模型。根据人的听觉的系统和批评乐队小浪变换的批评乐队的类似，水位标被嵌进低乐队并且数字小浪的中等带宽系数。嵌入的力量被掩盖的阀值适应地控制。嵌入的水位标信号是听不见的实验结果表演，和watermarked声音信号对象压缩那样的许多攻击有好坚韧性，噪音，重新采样，低通行证的过滤。

简介：在连续语音识别的音调模型集成的一个歧视的框架被建议。放大隐藏的Markov模型的可能性基于的方法使用模型依赖者重量光谱特征和音调模型基于音调的features.The重量是有区别地由最小的电话错误标准的trahined。模型重量的更改方程基于扩大Baum-Welch算法被导出。模型重量联合的各种各样的计划被评估，一种变光滑的技术被介绍成为训练对柔韧在适合上。建议方法是音调的音节输出和字符输出语音识别任务上的ewluated。试验性的结果证明建议方法由于给定的模型的更好的插值在二项任务比全球重量获得了9.5%和4.7%相对错误减小。这为音调模型集成证明歧视的训练模型重量的有效性。

简介：Time-frequencyanalysisiscombinedwitharrayprocessingtodevelopadirectionofarrival(DOA)estimationmethod.Thearraydatamodelisconstructedintime-frequencydomainbycrosstime-frequencydistributionbetweentheoutputofareferencesensorandthoseoftwosymmetricsub-arrays.Accordinglyasubspacemethodispresentedbasedontheaverageoftwosub-arrays'time-frequencydatavectormodelinsteadoftheconventionalarraymodel,toestimateDOAsofmultiplesignals.Becausethearraydataisprocessedbothinspatialdomainand2-Dtime-frequencydomain,theproposedmethodhasanabilitytoselectthesignalofinteresting,andissuitablefornon-stationarysignal.Additionally,themethodisrobusttonoiseandholdsanadvantageoflowcomputationalload.Simulationsareconductedtoverifytheefficiencyofthemethodandcomparisionismadewithothermethods.

简介：在分层的结构被获得的压电的底层和金属电影的声学的波浪的精确答案。阶段速度，机电的联合系数和静态的电容被计算在答案之上基于。陈和Hau是理论被用来分析表面声学的波浪在弄短与单身者一起的栅栏摸每个时期和一脱衣的思考系数表情被介绍。X112潦g上的铝的参数??膰？？

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简介：圆柱的超声的马达(CUSM)能广泛地在许多地例如里被使用激增并且集中照相机的系统，电的窗帘并且工作专注于的MEMS.This微司机单个点并且在定子和rotor.which之间的双点接触模式被理论证明，experiment.There是预先迫使在单个点的模型是的批评point.the下面的pre-pressure.When的一个批评的点合适；否则双点模型是appropriate.Then转的力量