Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/4882
標題: 基於語音轉換處理之極低位元率語音壓縮系統的研究與改進
Improvements of very low bit rate speech coding using speech transformation methods
作者: 林重佐
Lin, Chong-Zuo
關鍵字: LP-PSOLA
線性預測之基頻同步累加
Close-loop search algorithm
閉迴路式搜尋演算法
出版社: 通訊工程研究所
引用: [1]Marc Padellini, Francois Capman and Genevieve Baudoin”, Very low bit rate (VLBR) speech coding around 500 bits/sec” XII. European Signal Processing Conference, September, 2004. [2]Kechu Yi, Jun Cheng, Anliang Wang, Pu Zhang, Feng Liu, Weiying Li, Bin Yang, Shuanyi Du, Jim Gong,” A vocoder based on speech recognition and synthesis”, Global Telecommunications Conference, 1995. IEEE. GLOBECOM’95. [3]A.S.Spanias,” Speech Coding : A Tutorial Review,” Proceedings of the IEEE, vol.82, no.10, pp.1541-82, October 1994. [4]Thomas F. Quatieri ,” Discrete-Time Speech Signal Processing”, Pearson Education Taiwan Ltd. 2005. [5]SCHNELL,N. et al : Synthesizing a Choir in Real-Time using Pitch Synchronous Overlap Add(PSOLA), http//www.ircam.fr,dated 10/Sep/2006. [6]Moulines E. and Laroche J.,“ Non-Parametric techniques for pitch-scale and time-scale modification of speech.” Speech Communication 16 (1995) 175-205. [7]Srikanth Mangayyagari and Ravi Sankar “ Pitch Conversion Based on Pitch Mark Mapping” IEEE conferences 2007. [8]K. S. Rao and B. Yegnanarayana,“ Prosody modification using instants of significant excitation” IEEE Trans. Audio, Speech and Language Processing, vol. 14, pp. 972-980, May 2006. [9]WAI C. Chu,“ Speech Coding Algorithms Foundation And Evolution Of Standardized Coders”, Wiley-Interscience, 2003. [10] V. Ramasubramanian and D. Harish,“ An Optimal Unit-Selection Algorithm For Ultra Low Bit-Rate Speech Coding”, Speech and Signal Processing, PP.541-544, 2007. [11]K.S.Lee ,R. Cox,“ A Very Low Bit Rate Speech Coder Based On a Recognition/Synthesis Paradigm,” IEEE trans. SAP, Vol.9, No5, PP.482-491, July 2001. [12]G.Baudoin, F.El Chami,“ Corpus Based Very Low Bit Rate Speech Coding” Proc. ICASSP-03, PP.792-795, 2003. [13]Heng-Chou Chen, Chin-Yung Chen, Kui-Ming Tsou, Oscul T.-C. Chen,“ A 0.75 kbps Speech Codec Using Recognition and Synthesis Schemes”, Speech Coding For Telecommunications Proceeding, PP.27-28, 1997. [14]王小川,“ 語音訊號處理”, 全華 2005. [15]王建文,“ Very Low Speech Compression Using Closed-Loop Speech Transformation Merhods” 中興大學碩士論文, 2008.
摘要: 在目前通訊產品普及的時代,將有越來越多人透過無線傳輸的方式來進行溝通,由於傳輸頻寬的資源有限,使得在頻寬的使用上必需有效管理,因此極低位元壓縮率的語音編碼技術就顯的格外重要。在傳統基於線性預測之語音壓縮系統中,主要受限於預測誤差訊號的儲存需求,使得在極低位元率的語音壓縮下,很難保有原始語音的品質,因此利用相同發音的語音訊號,其具有高相關的特性,使得我們只需要儲存一組預測誤差,經有轉換後來產生其他相同發音的語音訊號,藉此將可以減少輸出的位元率,達成極低位元壓縮的目標。 本論文中,我們主要探討具有相同發音的語音壓縮處理,針對source訊號與target訊號各自的預測誤差,根據target的韻律參數來調整source預測誤差,使得調整後的訊號能近似target預測誤差。由於傳統的韻律調整方法,在多字詞的處理上,並未考量調整後的結果與實際target訊號之間的相關性,將可能導致訊號的失真,因此我們提出了閉迴路式搜尋演算法,針對target的每一個基頻週期,從source預測誤差中尋找最相近的週期訊號。此外,針對音高標記的方法,我們提出一致性的音高標記處理方法,來解決標記位置的偏移,導致比對後的結果存在很大的差異,然而在基頻週期的決策中,我們提出了間接搜尋法,來避免預測誤差經由合成濾波器可能產生的合成誤差累積之問題。最後我們則依據預測誤差搜尋後的結果與target預測誤差之間的差異,來重新計算合成濾波器係數,來降低對還原訊號的影響,對於還原訊號的影響。對於我們所提出的語音壓縮方法的改進,在語音訊號還原後的結果與實際target訊號之間的誤差平方和平均將能降低2~3dB。
URI: http://hdl.handle.net/11455/4882
其他識別: U0005-2008201013281200
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2008201013281200
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