Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech

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Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech

Persistent ID (NDL): info:ndljp/pid/9921980

Material type: 博士論文

Author: 劉, 麗清

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Publication date: 2015

Material Format: Digital

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Name of awarding university/degree: 埼玉大学,博士(工学)

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Note (General)：: type:textLinear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis ...

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Material Type: 博士論文
Title: Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech
Author/Editor: 劉, 麗清
Author Heading: 劉, 麗清
Publication Date: 2015
Publication Date (W3CDTF): 2015
Alternative Title: 音声のピッチ同期線形予測分析のための改善法
Periodical title: 博士論文（埼玉大学大学院理工学研究科（博士後期課程））
Degree grantor/type: 埼玉大学
Date Granted: 2015-03-24
Date Granted (W3CDTF): 2015-03-24
Dissertation Number: 甲第983号
Degree Type: 博士(工学)
Conferring No. (Dissertation): 甲第983号
Text Language Code: eng
Target Audience: 一般
Note (General): type:text
Linear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis due to its ability to model speech production process approximately. Hence LP analysis has been widely used for speech enhancement, low-bit-rate speech coding in cellular telephony, speech recognition, characteristic parameter extraction (vocal tract resonances frequencies, fundamental frequency called pitch) and so on. However, the performance of the conventional LP method is degraded by high-pitched harmonic structure of glottal excitation source and background noise. In order to improve the performance of LP analysis, it is necessary to reduce the effect of these two factors, which is a most challenging task for LP analysis.The objective of this dissertation is to develop some approaches to improve the performance of the LP analysis based on pitch synchronous analysis. We consider a pitch synchronous LP analysis for high-pitched speech using a weighted short time energy (STE) function for the purpose of downgrading the effect of the harmonic structure of the glottal excitation source. Unlike some conventional techniques, which require the electroglottography (EGG) signal or complicated epoch extraction algorithms, we utilize a simple STE computation of speech signal and prediction residual signal to extract the interval of glottal closed phase during a glottal cycle and do not need to estimate the instant of glottal closure and opening exactly.To reduce the infuence of the background noise, we propose a noise compensation LP method based on pitch synchronous analysis under white noise environment. Exploiting the periodicity of voiced speech and random distribution of background white noise, a more accurate estimation of noise power is calculated on each current frame of speech. The advantage, that the noise power is estimated from each current frame, can avoid the estimation delay and accuracy problem. Sometimes the background noise could be white or colored signals. A noise whitening method for the noise compensation LP Method is proposed so that the new noise estimator can be also applied to colored environment.We further propose a crosscorrelation sequence-based LP analysis under noisy environment. The crosscorrelation sequence is utilized to replace the original speech signal which is sensitive to background noise, and applied to LP analysis. The approach can improve the performance of LP analysis under noisy environment.In this dissertation, we focus on resolving the two factors that degrade the performance of LP analysis and new approaches have been proposed and implemented. The experimental results, based on synthetic and real speeches, demonstrate the effectiveness of the new approaches for improving the performance of the LP analysis.
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Introduction 161.1 Overview of LP analysis . . . . . . . . . . . . . . . . . . . . . . . . 171.2 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 181.3 Dissertation Organization . . . . . . . . . . . . . . . . . . . . . . . 192 Pitch Synchronous Linear Prediction Analysis of High-PitchedSpeech Using Weighted Short-Time Energy Function 202.1 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . 202.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212.3 STE Function Based on Residual Signal . . . . . . . . . . . . . . . 222.4 Pitch Synchronous Analysis Based on Weighted STE Function . . . 252.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 282.5.1 Results for Synthetic Speech Excited by Impulse Trains . . . 292.5.2 Results for Synthetic Speech Excited by Realistic Excitation 292.5.3 Results for Real Speech . . . . . . . . . . . . . . . . . . . . . 362.5.4 Stability of the Resulting All-Pole Filter . . . . . . . . . . . 392.6 Discussion and Summary . . . . . . . . . . . . . . . . . . . . . . . . 403 Noise Compensation LP Method Based on Pitch SynchronousAnalysis 423.1 Problem Description of Noise Compensation and Related Works . . 433.2 Noise Estimation Based on Pitch Synchronous Analysis . . . . . . . 453.2.1 Pitch Synchronization . . . . . . . . . . . . . . . . . . . . . 463.2.2 Enhanced Speech and Modified Noise Signals . . . . . . . . 473.2.3 Proposed Noise Estimator . . . . . . . . . . . . . . . . . . . 493.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 523.3.1 Simulation for Verifying the Proposed Noise Estimator . . . 523.3.2 Results using Synthetic Speech . . . . . . . . . . . . . . . . 533.3.3 Results using Real Speech . . . . . . . . . . . . . . . . . . . 553.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614 Pink Noise Whitening Method for Noise Compensation LP MethodBased on Pitch Synchronous Analysis 624.1 Constraint Problem of Noise Compensation . . . . . . . . . . . . . 624.2 Proposed Prediction Whitening Filter . . . . . . . . . . . . . . . . . 634.3 Improved PSAS Method . . . . . . . . . . . . . . . . . . . . . . . . 694.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 714.4.1 Results for Synthetic Speech . . . . . . . . . . . . . . . . . . 714.4.2 Results for Real Speech . . . . . . . . . . . . . . . . . . . . . 744.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 765 Linear Prediction Analysis of Crosscorrelation Sequence for VoicedSpeech 785.1 Problem Description of LP Analysis of Autocorrelation Sequence . . 795.2 LP Analysis of Crosscorrelation Sequence . . . . . . . . . . . . . . . 805.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 825.3.1 Results for Synthetic Speech . . . . . . . . . . . . . . . . . . 825.3.2 Results for Real Vowel . . . . . . . . . . . . . . . . . . . . . 835.4 Pitch Synchronous LP Analysis of Crosscorrelation Sequence . . . . 855.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 906 Conclusions 916.1 Summary of the Work . . . . . . . . . . . . . . . . . . . . . . . . . 916.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92A Discussion of Noise Power When K is Odd 93
指導教員 : 島村徹也
DOI: 10.24561/00010359
https://doi.org/10.24561/00010359
Persistent ID (NDL): info:ndljp/pid/9921980
https://dl.ndl.go.jp/pid/9921980
Collection: 障害者向け資料
Collection (Materials For Handicapped People:1): テキストデータ
Collection (particular): 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
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Acquisition Basis: 博士論文（自動収集）
Date Accepted (W3CDTF): 2016-04-01T14:32:40+09:00
Date Created (W3CDTF): 2015-12-16
Format (IMT): application/pdf
Access Restrictions: 国立国会図書館内限定公開
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Periodical Title (URI): http://dx.doi.org/10.24561/00010359
http://id.nii.ac.jp/1586/00010359/
Data Provider (Database): 国立国会図書館 : 国立国会図書館デジタルコレクション
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Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech

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