{"title":"Pitch detection in time and frequency domain","authors":"S. Upadhya","doi":"10.1109/ICCICT.2012.6398150","DOIUrl":null,"url":null,"abstract":"The beauty of human speech lies in the complexity of the different sounds that can be produced by a few tubes and muscles. This intricacy, however, makes speech processing a challenging task. One defining characteristic of speech is its pitch. Detecting this Pitch or equivalently, fundamental frequency detection of a speech signal is important in many speech applications. Pitch detectors are used in vocoders, speaker identification and verification systems and also as aids to the handicapped. Because of its importance many solutions to detect pitch has been proposed both in time and frequency domains. One such solution is pitch detection is by using Autocorrelation method and Average Magnitude Difference Function (AMDF), method which are analyses done in the time domain and the other is detecting the harmonic nature in the frequency domain. This paper gives the implementation results of the pitch period estimated in the time and frequency domains for vowel and fricative speech sounds, both for male and female speakers.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICT.2012.6398150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

The beauty of human speech lies in the complexity of the different sounds that can be produced by a few tubes and muscles. This intricacy, however, makes speech processing a challenging task. One defining characteristic of speech is its pitch. Detecting this Pitch or equivalently, fundamental frequency detection of a speech signal is important in many speech applications. Pitch detectors are used in vocoders, speaker identification and verification systems and also as aids to the handicapped. Because of its importance many solutions to detect pitch has been proposed both in time and frequency domains. One such solution is pitch detection is by using Autocorrelation method and Average Magnitude Difference Function (AMDF), method which are analyses done in the time domain and the other is detecting the harmonic nature in the frequency domain. This paper gives the implementation results of the pitch period estimated in the time and frequency domains for vowel and fricative speech sounds, both for male and female speakers.
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时域和频域的基音检测
人类语言的美妙之处在于不同声音的复杂性,这些声音可以由一些管子和肌肉发出。然而,这种复杂性使得语音处理成为一项具有挑战性的任务。语音的一个决定性特征是音高。在许多语音应用中,检测该基音或等效的语音信号的基频检测非常重要。音高检测器用于声码器、说话人识别和验证系统,也可作为残疾人的辅助工具。由于基音检测的重要性,人们从时域和频域两方面提出了许多基音检测方法。其中一种方法是利用自相关法和平均幅值差函数(AMDF)在时域进行分析,另一种方法是在频域进行谐波检测。本文给出了在时间域和频率域估计元音和摩擦音的音高周期的实现结果,包括男性和女性说话者。
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