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姓名 陳柏仁(Bo-ren Chen) 查詢紙本館藏 畢業系所 電機工程學系 論文名稱 應用投票演算法之語者確認系統研究
(The Application of Voting to the Speaker Verification System)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 本論文使用一種新的分數計算方法—投票演算法(Voting),藉由此方法應用於語者確認系統上,使得語者確認系統的效能得到提升。
本論文將投票演算法與分數正規化(Test Normalization)結合,提出了四種新的語者確認系統架構,其中以改善混合式語者確認系統可以達到最大改善。實驗結果顯示,系統性能可達最好的相等錯誤率及決策成本函數為9.28%和0.1132,比起傳統的語者確認系統的效能12.53%和0.1534,改善了3.25%和0.0402;比起分數正規化式語者確認系統的效能9.87%和0.1154,改善了0.59%和0.0022。
本論文利用新的分數計算方法Voting,所提出的語者確認系統架構可以輔助分數正規化式語者確認系統,提供語者資訊,使系統性能達到改善。摘要(英) This thesis uses a kind of new score computing –Voting, making use of it on the speaker verification system and the efficiency of speaker verification system is improved.
We combine Voting and Test normalization and four new kinds of speaker verification system are proposed, improved hybrid speaker verification system can reach the greatest improvement. The experimental result shows, improved hybrid speaker verification system compare with the traditional speaker verification system that EER can be up to 3.25% and DCF can be up to 0.0402 of the improvement. Improved hybrid speaker verification system compare with the test normalization speaker verification system that EER can be up to 0.59% and DCF can be up to 0.0022 of the improvement.
The new speaker verification system we propose may assist with test normalization speaker verification system. The new system can supply speaker information and improve the efficiency of speaker verification system.關鍵字(中) ★ 語者確認 關鍵字(英) ★ speaker verification 論文目次 摘要...........................Ⅰ
目錄...........................Ⅲ
附圖目錄.........................Ⅵ
附表目錄.........................Ⅶ
第一章 緒論
1.1 研究動機...................... 1
1.2 語者辨識系統概述..................2
1.3 研究方向......................4
1.4 章節概要...................... 4
第二章 語音處理與語者辨識基本技術
2.1 特徵參數擷取.................... 5
2.2 語者模型建立.................... 7
2.2.1高斯混合語者模型...............8
2.2.2 語者模型訓練流程............... 9
2.2.3 向量量化................... 10
2.2.4 EM演算法.................. 13
2.3 貝式調適法..................... 14
2.4 語者辨識...................... 19
2.5 語者確認..................... 20
2.6 相等錯誤率與偵測錯誤交易曲線圖.......... 21
第三章 系統架構
3.1 分數正規化..................... 23
3.2 投票演算法..................... 25
3.3 語者確認系統.................... 27
3.3.1 投票式語者確認系統..............28
3.3.2 混合式語者確認系統..............29
3.3.3 改善投票式語者確認系統............30
3.3.4 改善混合式語者確認系統............31
第四章 語者辨識實驗之研究
4.1 語音資料庫..................... 32
4.2 投票演算法應用於語者確認系統............ 33
4.2.1 實驗一.................... 34
4.2.2 實驗二.................... 36
4.2.3 實驗三.................... 39
4.2.4 實驗四.................... 41
第五章 結論與未來展望
5.1 結論........................ 44
5.2 未來展望...................... 46
參考文獻.........................47參考文獻 [1] A. Martin, G. Doddington, T. Kamn, M. Ordowski, and M, Przybocki, “The DET curve in assessment of detection task performance,” in Proceedings of European Conference on Speech Communication and Technology, pp. 1895-1898, 1997.
[2] B. Narayanaswamy, R. Gangadharaiah, “Extracting Additional Information from Gaussian Mixture Model Probabilities for Improved Text-Independent Speaker Identification,” Acoustics, Speech, and Signal Processing, vol. 1, pp 621-624, 2005.
[3] C. Auckenthaler, Lloyd-Thomas, “Score Normalization for Text-independent Speaker Verification System,” Digital Signal Processing, vol. 10 No1-3, 2000.
[4] C. P. Chen and J. Bilmes, “MVA Processing of Speech Features”, Audio, Speech and Language Processing, vol. 15, pp257-270, 2007.
[5] D. A. Reynolds and R. C. Rose, “Robust Text-Independent Speaker Identification Using Gaussian Mixture Models,” IEEE Trans. Speech and Audio Processing, vol. 3, no. 1, pp. 72-83, January 1995.
[6] D. Reynolds and T. Quatieri, “Speaker Verification Using Adapted Gaussian Mixture Models,” Digital Signal Processing 10, PP. 19-41, 2000.
[7] J. T. Tou, R. C. Gonzalez, Pattern Recognition Principles, Addison Wesley, 1974.
[8] L. R. Rabiner and B. H. Juang, Fundamentals of Speech Recognition, Prentice Hall, New Jersey, 1993.
[9] L. S. Lee, Y. Lee, “Voice Access of Global Information for Broad-Band Wireless: Technologies of Today and Challenges of Tomorrow,” Proceedings of the IEEE, vol. 89, no. 1, pp. 41-57, January 2001.
[10] R. Vergin and D. O’Shaughnessy and A. Farhat, “Generalized Mel Frequency Coefficients for Large-Vocabulary Speaker-Independent Continuous-Speech Recognition,” IEEE Trans. Speech and Audio Processing, vol. 7, no. 5, pp. 525-532, September 1999.
[11] T. K. Moon, “The Expectation-Maximization Algorithm,” IEEE Signal Processing Magazine, vol. 13, no. 6, pp. 47-60, November 1996.
[12] X. Huang, A. Acero and H. W. Hon, Spoken Language Processing, Prentice Hall, 2001.
[13] 吳金池, “語者辨識系統之研究”,國立中央大學電機工程研究所碩士論文,民國九十一年。
[14] 賴彥輔, “語者辨識之研究”,國立中央大學電機工程研究所碩士論文,民國九十二年。指導教授 莊堯棠(Yau-Tarng Juang) 審核日期 2007-7-3 推文 plurk
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