麥克風陣列語音分離硬體加速器設計

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高亦文(Liszt Kao) 查詢紙本館藏

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資訊工程學系在職專班

論文名稱

麥克風陣列語音分離硬體加速器設計
(Voice Signal Separated Accelerator with Microphone Array)

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摘要(中)

傳統Fast ICA的獨立成份分析(Independent Component Analysis, ICA)方法會面臨兩種缺點，一個是獨立成份的順序無法決定，另一個是Fast ICA也僅限於解決靜態資料。為了要避免這樣的問題，本研究提出一種基於Robust ICA與頻域訊號分離改進的方法。Robust ICA是一種利用四次多項式的根來尋找分離矩陣，達到收斂效果以求得獨立成份，提供了複數運算的支援並減少白化的過程。將ICA的操作過程放到頻域中執行可以將龐大的問題分成好幾個子問題個別處理，利用硬體平行處理的特性同時分離好幾個聲音段可以加快語音訊號分離處理速度，另外一個好處是在頻域中非高斯的情況會比時域中更加明顯。實驗結果可以發現，基於此架構設計出的語音訊號分離硬體加速器可以解決語音訊號順序不確定的問題，達到語音訊號批次處理的效果。在語音訊號執行速度上，語音訊號分離的處理速度比軟體快，並可以解決實驗中無法達到的語音即時處理的效果。

摘要(英)

The traditional independent component analysis of FastICA faces two of disadvantages, undetermined component of order and offline experiment. We proposed a new solution by using RobustICA algorithem with demixing signal in the frequency domain. RobustICA separate independent component by searching demixing vector and using four degree polynomial, supporting complex calculation without whitening progress. The progress which separated component in frequency domain will speed up separated by divided a bunch data into frequency bin with hardware characteristic of parallel process. Moreover, the Non-Gaussianity is obviously in frequency domain. Its shows in experiment that the voice signal separated accelerator have many characteristics including batching progress, ordering component and real time signal separated process.

關鍵字(中)

★ 麥克風陣列語音分離硬體加速器設計
★ 麥克風陣列
★ 語音分離

關鍵字(英)

論文目次

摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 viii
第一章緒論 1
1.1研究動機 1
1.2論文架構 4
第二章語音訊號演算法 5
2.1 麥克風陣列 5
2.2 語音訊號截取 6
2.2.1 PDM訊號 7
2.2.2 Cascaded Integrator-Comb 演算法 8
2.3語音訊號分離 13
2.3.1 獨立成份分析(ICA) 13
2.3.2 Fast ICA演算法 21
2.3.3 Robust ICA演算法 22
2.3.4頻域盲訊號分離 23
第三章語音訊號處理設計 25
3.1 系統設計與高階合成方法論 25
3.1.1 IDEF0 26
3.1.2 GRAFCET 27
3.1.3 合成規則 30
3.2 系統架構設計 32
3.3 CIC演算法降頻模組 35
3.4 預處理模組 38
3.5 ICA分離成份模組 41
3.6 頻域盲訊號處理模組 44
3.7 複數與浮點數 47
3.8 管線化硬體架構設計 48
第四章系統整合驗證與實驗 50
4.1 實驗設備與開發環境 50
4.2 語音訊號擷取實作與驗證 52
4.3語音訊號分離實作與驗證 56
4.3.1實驗資料與硬體資源使用情況 56
4.3.2局部管線化處理使用 57
4.3.3實驗結果 58
第五章結論與未來方向 62
5.1 結論 62
5.2未來研究方向 63
參考文獻 64

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指導教授

陳慶瀚

審核日期

2014-7-14

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