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研究生:王煌仁
研究生(外文):Huang-Jen Wang
論文名稱:環境控制輔具之語音辨識系統設計
論文名稱(外文):Speech Recognition System Design of Environment Control Auxiliary Equipment
指導教授:陶金旭
指導教授(外文):Jin-Shiuh Taur
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:72
中文關鍵詞:語音辨識隱藏式馬可夫麥克風陣列
外文關鍵詞:Speech RecognitionHidden Markov ModelMicrohpone Array
相關次數:
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  • 收藏至我的研究室書目清單書目收藏:5
中文摘要
本論文為國科會環境控制輔具計畫之語音控制的主要部份,其目的是發展一套適合行動不便之病患,以語音辨識的方式來控制其生活周遭的家電用品,以營造舒適的生活機能。
在本文中,我們設計了兩套系統,一套是使用一般麥克風的語音辨識系統,另外一套則為麥克風陣列語音辨識系統。
一般麥克風的語音辨識系統中,使用越零率、能量方法將有效語音段切割出來,而麥克風陣列語音辨識系統中,則計算出語音到達每個麥克風的延遲時間後,使用Delay and Sum Beamformer將語音訊號加強,最後兩個系統皆用MFCC擷取出語音的特徵參數,並使用隱藏式馬可夫模型做為語音辨識。
Abstract
This paper develops a system for patients with physically disabling. With the use of speech recognition, the patient can control the electrical appliances conveniently in daily life.
In this thesis, two systems of the speech recognition were designed. One isthe general microphone speech recognition system, and the other is the microphone array system.
In contrast with the general microphone speech recognition system, the microphone array system calculates the delay time of each microphone and then use delay time and beamformer to enhance the speech signals rather than use the zero-crossing rate and energy to segment the speech signal.
After that, the MFCC is used to extract the feature parameters of speech signals in both systems. Then the Hidden Markov Model is adopted to recognize the speech signals.
目 錄
中文摘要.............................................. i
Abstract ..............................................ii
誌謝...................................................iii
目錄...................................................iv
圖目錄.................................................vii
表目錄.................................................ix
第一章 緒論............................................1
1.1 研究動機..........................................1
1.2 環境控制系統介紹..................................2
1.3 章節大要..........................................3
第二章 語音辨識的基礎理論..............................4
2.1預強調 ..............................................4
2.2 分框處理...........................................5
2.3 語音端點偵測.......................................6
2.4 加窗處理...........................................9
2.5 特徵參數擷取.......................................10
2.5.1 MFCC(Mel-Frequency Cepstral Coefficients) .......11
2.6 隱藏式馬可夫模型...................................14
2.6.1 隱藏式馬可夫模型之建立...........................15
2.6.2 機率計算.........................................16
2.6.3 前算程序.........................................17
2.6.4 後算程序.........................................19
2.6.5 維特比演算法 .....................................20
2.6.6 參數重估(Parameter Reestimation) ................23
2.6.7 語音模型的建立...................................25
第三章 單支麥克風語音辨識系統..........................26
3.1聲音偵測............................................27
3.2 錄音...............................................28
3.3前置處理及有效語音切割..............................28
3.4 特徵參數擷取.......................................28
3.5 訓練隱藏馬可模型...................................28
3.6 辨識...............................................28
第四章 麥克風陣列語音辨識系統..........................30
4.1麥克風陣列..........................................31
4.2 訊號放大器.........................................36
4.3 訊號擷取卡.........................................38
4.4 訊號處理...........................................41
第五章 實驗結果與比較..................................49
5.1實驗方法............................................50
5.2.1 單支麥克風無雜訊環境下之辨識率...................49
5.2.2 單支麥克風雜訊環境下之辨識率.....................50
5.2.3 16支麥克風陣列無雜訊環境下之辨識率...............60
5.3 麥克風陣列之聲源偵測...............................67
第六章 結論與未來展望..................................69
6.1 結論...............................................69
6.2 未來展望...........................................69
參考文獻...............................................70
參考文獻
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