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基于多相滤波器组的语音基频检测方法 被引量:1

A More Accurate Pitch Detection Algorithm (PDA)
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摘要 基于多相滤波器组的语音基频检测方法 ,运用多相滤波器组分解语音信号频谱 ,然后利用声带震动的能量准周期性在各子带进行峰值搜索 ,并综合这些子带的搜索结果计算基音周期 ,最后根据先验知识以及一种新的清浊音判定方法对结果进行校正。基于标准 Past PDAs, to our best knowledge, were unable to predict accurately the pitch at any instant. We now propose a PDA based on multi phase filter bank that can do so. Section 1 discusses in much detail the design of multi phase filter bank. Essentially it explains how to decompose the speech spectrum for removing vocal tract effects. Fig.1 shows the prototype low pass filter. Section 1 also gives the procedure of bandwidth selection. Section 2 discusses in much detail the procedure for pitch detection. Essentially it performs peak searching in each sub band and gets decision for each sub band; it synthesizes all the sub band decisions to obtain the final detection results. Section 2 also gives the rules for correct peak searching. Section 3 proposes a new method for making voiced/unvoiced decision based essentially on the following fact: the energy spectrum of the voiced speech is different from that of the unvoiced speech. Experimental results given in section 4 on sentences chosen from TIMIT database show preliminarily that out new PDA based on multi phase filter bank can predict accurately the pitch at any instant.
出处 《西北工业大学学报》 EI CAS CSCD 北大核心 2003年第5期603-606,共4页 Journal of Northwestern Polytechnical University
基金 陕西省自然科学基金 (2 0 0 3CS110 1) 西北工业大学博士论文创新基金 (2 0 0 2 35 )
关键词 基音频率检测 多相滤波器组 峰值搜索 Pitch Detection Algorithm(PDA), multi phase filter bank, peak searching
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参考文献5

  • 1Hess W H. Pitch Determination of Speech Signals: Algorithms and Devices. Heidelberg, Germany: Springer-Verlag,1983.
  • 2Rabinter L R, et al. A Comparative Performance Study of Several Pitch Detection Algorithms. IEEE Trans Acoust Speech Signal Processing, 1976, 24(5): 399~418.
  • 3McCree A V. A Mixed Excitation LPC Voeoder Model for Low Bit Rate Speech Coding. IEEE Transactions on Speech and Audio Processing, 1995, 3(4):242~250.
  • 4Ancin F J, et al. A Novel DyWTVT Approach for Continuous Speech Pitch Estimation. In Proceedings EUSIPCO,1994, 3:1677~1680.
  • 5Harris F J. On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform. Proceedings of the IEEE. 1978, 66:51~84.

同被引文献6

  • 1FOTINEA S E,BAKAMIDIS S,ATHANASELIS T,et al.Emotion in speech:towards an integration of linguistic,paralinguistic,and psychological analysis[C]//Proc of International Conference on Spoken Language Processing.Berlin,Heidelberg:Springer-Verlag,2003:1125-1132.
  • 2JIANG Dan-ning,CAI Lian-hong.Speech emotion classification with the combination of statistic features and temporal features[C]//Proc of ICME.2004:1967-1970.
  • 3MERAL H M,EKENEL H K,OZSOY A S.Role of intonation patterns in convering emotion in speech[C]//Proc of International Conference on Phonetic Sciences.San Francisco:USA Murray,I.R,1999:2001-2004.
  • 4VERVERIDIS D,KOTROPOULOS C,PITAS I.Automatic emotional speech classification[C]//Proc of IEEE International Conference on Acoustics,Speech,and Signal Processing.2004:593-596.
  • 5CHUANG Ze-jing,WU C H.IG-based feature extraction and compensation for emotion recognition from speech[C]//Proc of Affective Comuting and Intelligent(ACII).Berlin:Springer-Verlag,2005:358-363.
  • 6VALERY A P.Emotion recognition in speech signal:experimental study,development,and application[C]//Proc of International Conference on Spoken Language Processing.2000:222-225.

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