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ID:8320433
大小:1.30 MB
页数:33页
时间:2018-03-19
《语音基音周期检测算法比较》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、本科毕业论文题目语音基音周期检测算法比较学院管理科学与工程学院专业电子信息工程班级081信工(1)班学号姓名指导老师二〇一二年六月语音基音周期检测算法比较摘要基音周期作为语音信号处理中描述激励源的重要参数之一,广泛的应用于语音合成、语音编码和语音识别等语音信号处理等技术领域。准确可靠的对基音周期进行检测将直接影响整个语音处理系统的性能。常用的基音检测算法对于纯净语音信号都能达到较好的检测效果。然而,实际当中的语音信号不可避免的会受到外界背景噪音的影响,使得这些检测算法的检测效果都不是很理想,为此本文用两种基本算法对语音信号滤波前后进行基音周期检测,在进行比较。论文首先介绍了语音基音检测算法的
2、研究背景极其重要意义。其次对现有的基音检测算法进行了归纳和总结,并详细的介绍本文将用的两种基本基音检测算法的基本原理及实现。最后在Matlab上对语音信号进行基音周期检测。论文还完成了算法的程序设计,在Matlab7.0仿真环境下,对上诉算法进行仿真验证,并且在滤波前后做了对比实验。实验结果表明,经过滤波的语音信号基音周期检测的更加准确。关键词:基音检测;自相关函数法;平均幅度差函数法;基音轨迹AbstractPitchasinspeechsignalprocessingisoneoftheimportantparameterstodescribetheexcitationsource,wi
3、delyusedinspeechsynthesis,speechcodingandspeechrecognitionspeechsignalprocessingtechnology.Accuratepitchperioddetectionwilldirectlyaffecttheperformanceofthespeechprocessingsystem.Commonlyusedalgorithmforpitchdetectionforcleanspeechsignaltoachievegooddetectioneffect.However,theactualspeechsignalwill
4、beinevitablyinfluencedbyexternaleffectsofbackgroundnoise,sothedetectionalgorithmtodetecttheeffectisnotveryideal,thepaperusetwobasicalgorithmsbeforeandafterfilteringthespeechsignalpitchdetection,incomparison.Thethesisfirstintroducestheresearchbackgroundofspeechpitchdetectionalgorithmisveryimportant.
5、Nexttotheexistingalgorithmforpitchdetectionaresummarized,andadetailedintroductiontothisarticlewillusethetwokindsofbasicpitchdetectionalgorithmisthebasicprincipleandrealization.FinallyinMatlabonspeechsignalpitchperioddetection.Thepaperalsofinishedprogrammingalgorithm,intheMatlab7.0simulationenvironm
6、ent,thealgorithmisvalidatedbysimulation,andthecontrastexperimentsweredonebeforeandafterfiltering.Theexperimentalresultsshowthat,afterthefilteringofthespeechsignalpitchperioddetectionismoreaccurate.Keywords:pitchdetection;autocorrelationfunction;theaveragemagnitudedifferencefunctionmethod;pitchcontr
7、ail目录第1章绪论······················································11.1引言··························································11.2基音检测的定义和意义··········································11.3基音检测的研究现状·········
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