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研究生: 林文雄
Lin, Wun-Syong
論文名稱: 基於AMDF音高特徵演算法之非特定語者單一詞彙語音確認嵌入式系統設計與實現
An Embedded System Design and Implementation for Speaker Independent Single-Words Speech Verification using AMDF-based Pitch Features
指導教授: 王駿發
Wang, Jhing-Fa
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 65
中文關鍵詞: AMDF音高偵測非特定語者AGC嵌入式系統
外文關鍵詞: AMDF, Pitch Detection, Speaker Independent, AGC, Embedded System
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  • 人機互動系統之語音介面不僅提供了使用者友善的介面,也提供了系統一種可回饋使用者的反應機制。在本研究中利用單一詞彙語音確認與音高週期來設計一套嵌入式語音介面系統,以提高語音互動人機介面在嵌入式系統的功能性與實用性。本研究所提出的嵌入式語音介面系統可以在現有嵌入式硬體資源的條件下完成設計,使其具有小尺寸、低成本、低功率、即時性、高量產化,易應用於任何現有的互動式產品上。
    在音高週期估測方法中,論文採用平均振幅差函數(Average Magnitude Difference Function, AMDF)求取所需的音高週期語音特徵用於語音確認。透過實驗,AMDF的音高週期在較低的計算量情況下仍具有極高的可靠性。進一步改良AMDF的運算量,降低其運算量需求,並維持原有的準確性。本論文除了研究音高週期特徵擷取之外,音高週期特徵辨識亦設計在嵌入式系統上。
    本論文亦提出一個以AMDF的音高週期特徵與有限狀態機(Finite State Machine)之低成本的語音辨識互動嵌入式系統。在不同距離與相同環境下,1組2秒正確命令與1組2秒錯誤命令,該系統辨識正確率大約可達95%,以達到非特定語者之語音辨認。本系統除了包含前置放大電路、AGC、濾波電路亦實現音高特徵擷取的功能。未來可廣泛應用於人機語音互動系統,例如鬧鐘、智慧型玩具、即時回饋系統以及聲控遙控器等等。

    Speech Interface of human-machine interactive system provides not only friendly interface but also a directly feedback mechanism for user. In this thesis, an embedded system is designed and implemented with using the pitch-based single-words speech verification to promote the functionality for speech interactive interface. The proposed system is especially designed for the hardware resource limitation environment, and it has the following features: small size, low cost, low power consumption, real-time operation, and can be widely applied to speech interactive applications.
    In pitch detection, the average magnitude difference function (AMDF) is adopted to predict the pitch period feature for speaker independent utterance verification. We propose an upper bound strategy to reduce the iteration times of SAA (subtraction absolute operation and accumulation), and this new manner can reduce the computations power with high AMDF accuracy. The proposed pitch period feature extraction manner is implemented on an embedded system with 8051 MCU, preamplifier circuit, AGC and filtering circuit. For single command of 2 seconds duration speech data, the average speech verification accuracy rate is about 95% under difference distances from speaker to microphone. From experimental results, we found that the detected pitch period from the modified AMDF is still reliable.
    The proposed prototype can be widely applied to human-machine interactive system, such as alarm clock, intelligent toys, real-time feedback system, and hand-free remote controller, etc.

    中文摘要 III ABSTRACT V ACKNOWLEDGEMENTS VII CONTENTS VIII LIST OF FIGURES X LIST OF TABLES XIII Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Thesis Objective 2 1.3 Thesis Organization 2 Chapter 2. Previous Works 4 2.1 History of Speech Single Processing 4 2.2 Trend of Single-Words Speech Verification 4 2.3 Pitch Detection of Single-Words Speech Verification 5 2.4 System Blocks 6 Chapter 3. Single-Words Speech Verification Algorithm 8 3.1 Algorithm Overview 8 3.1.1 Frame Blocking 9 3.1.2 Energy Calculation 9 3.1.3 Zero-crossing rate 10 3.2 AMDF-based Pitch Feature Extraction 11 3.2.1 Introduction to AMDF algorithm 11 3.2.2 Improvement of effective AMDF 14 3.3 Pitch Estimation 17 3.4 Pitch Contour Boundary Identification (PCBI) 19 3.5 Verification using FSM 20 Chapter 4. Embedded System Design of the Proposed Speech Verification 21 4.1 Hardware Circuit 22 4.1.1 Input Circuit 22 4.1.2 Output Circuit 26 4.2 Actual development Circuit 28 4.3 Hardware Platform for Embedded System 35 4.3.1 Hardware Block Description 36 4.3.2 CIP-51™ Microcontroller Core 37 4.3.3 JTAG Debug and Boundary Scan 39 4.3.4 On-Chip Memory 40 4.3.5 12 or 10-Bit Analog to Digital Converter 42 4.3.6 8-Bit Analog to Digital Converter 44 4.3.7 DACs, 12-Bit Voltage Mode 45 4.3.8 Programmable Digital I/O and Crossbar 47 4.3.9 Phase-Locked Loop (PLL) 49 4.4 Memory Allocation 53 Chapter 5. System of Software and Hardware Integration 54 5.1 Algorithm Evaluation of the Software 54 5.2 Introduction to the Environment Verification of the System 56 5.3 Recognition Rate of Test for Chinese and English Statement under the Specific Environment 57 Chapter 6. Conclusions and Future Works 60 REFERENCES 61 Appendices. 63 Appendix1 Hardware Circuit 63 Appendix2 Actual development Circuit 64

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    [02] Jyan Yi Du, Jhing-Fa Wang, “An Embedded System Design for Speech Recognition using Improved AMDF-based Pitch Features,” Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C. (2007).
    [03] Jyh-Shing Roger Jang, “Audio Signal Processing and Recognition,” (in Chinese) available at the links for on-line courses at the author's homepage at http://neural.cs.nthu.edu.tw/jang/books/audioSignalProcessing/
    [04] Om Deshmukh, Carol Y. Espy-Wilson, Ariel Salomon, and Jawahar Singh, “Use of Temporal Information: Detection of Periodicity, Aperiodicity, and Pitch in Speech,” IEEE Transactions, Speech and Audio Processing, Vol. 13, Issue 5, Part 2, pp. 776 – 786, Sep 2005.
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    [07] Xu Gang, Tang Liang-rui, “Speech pitch period estimation using circular AMDF,” Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003. 14th IEEE Proceedings, pp. 2452 – 2455, vol.3, 2003.
    [08] Yu-Min Zeng, Zhen-Yang Wu, Hai-Bin Liu, Lin Zhou, “Modified AMDF pitch detection algorithm,” Machine Learning and Cybernetics, 2003 International Conference, pp. 470 – 473, vol.1, 2003.
    [09] Jin-Wang Chen, Chuan-Kai Yang, “A Pitch Extraction Method Based on the AMDF Algorithm,” Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, R.O.C. (2007).
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    [13] 王小川,語音訊號處理,2nd Edition,全華科技圖書股份有限公司,台北,2007.

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