Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/18058
標題: 利用權重式共同向量法於中字彙之特定語者中文單音辨識
Using the Method of Weighted Common Vector to Recognize Isolated Mandarin Word for Speaker-Dependent System
作者: 羅璟義
Lo, Jing-Yi
關鍵字: Common Vector;共同向量;Weighted;權重
出版社: 應用數學系所
引用: [1]. 王小川 (2004)。"語音訊號處理"。台北市:全華。 [2]. 王國榮 (2000)。" Visual Basic 6.0 實戰講座"。台北巿:旗標。 [3]. 李宗寶,林靖剛 (2006)。"利用Multiple Common Vector 於國語數字之語音辨識"。碩士論文,國立中興大學應用數學研究所,台中。 [4]. 李宗寶,杜思良 (2008)。"利用共同向量於特定語者中文單音辨識"。碩士論文,國立中興大學應用數學研究所,台中。 [5]. 吳明哲,黃世陽 (1998)。Visual Basic 6.0 中文版學習範本。台北市:松崗。 [6]. Angm, H (1995), “Common vector obtained from linearly independent speech vectors by using LPC parameters”, Graduation project, Elect. Electron. Eng. Dept., Osmangazi Univ., Eskisehir, Turkey. [7]. Bing, X. and Yihe, S. (1996), “Research on ASIC for multi-speaker isolated word recognition”, ASIC, 2nd International Conference, pp. 135-137. [8]. Gulmezoglu, M.B , Vakif Dzhafarov, and Atalay Barkana (1999), “ A novel approach to isolated word recognition”, IEEE Trans. On Speech and Audio Processing, vol. 7. No. 6. [9]. Harb, H. and Husseiny, A.H. (2000), “Isolated words recognition using neural networks,” The 7th IEEE International Conference on, 1, pp. 349-351. [10]. Keskin, M. Gulmezoglu, M. B. Parlaktuna, O. and Barkana, A. (1996), “Isolated word recognition by extracting personal differences”, in Proc. 6 th Int.Conf. Signal Processing Applications and Technology, Boston, MA , pp. 1989-1992. [11]. Li, T.F. (2003), “Speech recognition of mandarin monosyllables”, Pattern Recognition 36, pp. 2713-2721. [12]. Rabiner, L.R. and Sambur, M.R. (1975), “An algorithm for determining the endpoints of isolated utterances”, The Bell System Technique Journal,Vol.54, pp. 297-315. [13]. Sakoe, H. and Chiba, S. (1978), “Dynamic Programming Optimization for Spoken Word Recognition”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 26, pp. 43-49. [14]. Yucel, S. (1996), “Application of Gram-Schmidt orthogonalization method to speech recognition for different noise levels” graduation project, Elect. Electron. Eng. Dept., Osmangazi Univ., Eskisehir, Turkey. [15]. Rabiner, L.R. and Sambur, M.R. (1975), “An algorithm for determining the endpoints of isolated utterances”, The Bell System Technique Ournal,Vol.54, pp. 297-315.
摘要: 
本篇論文主要是探討200個國字單音的辨識,首先利用共同向量來建構出語音模型,之後試著分不同的前後音框數以及不同的權重下,觀察在哪一種的前後音框數和權重下會有最好的辨識率,本論文討論的其他三個實驗因子:「語音的音框數」、「前後的音框數」、「權重」,希望能找出在何種情況下200個字能具有不錯的辨識率,在本論文的實驗結果,辨識200個字最高辨識率為91.67%。

This paper is to discuss the speech recognition of 200 isolated mandarin words. At first, we use the method of common vector to construct the speech model. Then, we will try to choose which first several frames and latter several frames and the weighted, if it can improve the rate of recognition. We consider the other three experimental factors in this paper: “the number of frame”, “ first several frames and latter several frames”, “the weighted”. We hope to find out the circumstances under which the 200 characters can be a good discrimination. We hope to find out which cirsumstances for the recognition of 200 words would be the best. And the maximum rate of recongntion attains 91.67% on the 200 words.
URI: http://hdl.handle.net/11455/18058
其他識別: U0005-0207200914074300
Appears in Collections:應用數學系所

Show full item record
 

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.