用類神經網路研究中文語音聲調產生之神經關聯性

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研究生：	王韜維 Tao-Wei Wang
論文名稱：	用類神經網路研究中文語音聲調產生之神經關聯性 Study of Neural Correlates on Chinese Tones by Neural Network Model
指導教授：	吳炤民 Chao-Min Wu
口試委員:
學位類別：	碩士 Master
系所名稱：	資訊電機學院 - 電機工程學系 Department of Electrical Engineering
畢業學年度：	97
語文別：	中文
論文頁數：	76
中文關鍵詞：	功能性磁振照影、聲調、類神經網路
外文關鍵詞：	Neural Network Model, tone, fMRI
相關次數：	點閱：11 下載：0
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中文聲調在語言學上，已被確定與語詞和句子的辨識度有關。但是在神經心理學方面，有關聲調產生的大腦功能區仍有爭議性。因此本研究的目的是要用類神經網路來研究中文語音聲調產生之神經關聯性。本研究改良以類神經網路理論為基礎的模型-DIVA模型(Directions Into Velocities Articulator)做為工具，使DIVA模型可以產生不同聲調的中文語音並產生模擬的大腦活化區。模擬結果（相同聲調不同母音（/u/－/a/）和不同母音相同聲調之學習（/i/－/a/））顯示改良後的模型可以產生不同的聲調以及維持原本的功能。進一步模擬產生相同母音不同聲調時（ㄚ、ㄚˊ、ㄚˇ、ㄚˋ）的結果顯示在DIVA設定的運動區與運動前區中，喉嚨的位置以及感覺區會有不同的活化顯示。這些活化區和臨床實驗結果類似，顯示改良後的DIVA模型具有探討中文聲調之神經關聯的功能。

In linguistics, Chinese tone is related to the Chinese word and sentence recognition rates. Neuropsychologically, issues of neural correlates on Chinese tone are still inconclusive. The purpose of this study is to investigate neural correlates on Chinese tone using a Neural Network Model – DIVA model ( Directions Into Velocities Articulator) . This study modified the original DIVA model to include additional tone production to simulate Chinese tone production and the resulted brain activation. Simulated results (different vowels with the same tone ( /a/ - /u/ ) and training process of different vowels with the same tone (/a/ - /i/)) verified new functions of the modified DIVA model. Further simulation on the same vowel with four different Chinese tones production(ㄚ、ㄚˊ、ㄚˇ、ㄚˋ)were implemented and compared to the results of published clinical studies. Similar brain activation areas were found on the larynx area in the motor cortex, pre-motor, and somatosensory cortices set by the DIVA model. These simulated results show that the improved DIVA model could be used to study the neural correlates on Chinese tone production.

中文摘要.....................................................................................................I
關鍵字：聲調、功能性磁振照影、中文聲調........................................I
Abstracr......................................................................................................II
目錄...........................................................................................................III
圖目錄......................................................................................................VI
第一章 緒論........................................................................................1
1研究動機：....................................................................................1
2說話的生理：................................................................................2
3語音產生的模型............................................................................4
4 聲調的探討...................................................................................9
5文獻探討......................................................................................10
5.1大腦與說話的神經關聯....................................................11
5.2 DIVA模型..........................................................................14
7 論文內容架構.............................................................................16
第二章 神經網路..............................................................................18
0類神經網路..................................................................................18
1 感知器（perceptron）...............................................................20
2線性濾波器..................................................................................21
3倒傳遞網路(backpropagation)....................................................23
3徑向基網路(radial basis network)...............................................26
4學習向量量化網路(learning vector quantization , LVQ)...........27
5自組織特徵映射圖類神經網路(self – organizing)....................30
第三章 DIVA 模型...........................................................................32
1 Maeda 模型............................................................................32
2 DIVA模型................................................................................33
2.1運動前區和運動區............................................................37
2.1.1運動前區與語音目標.....................................................37
2.1.2運動區，速度及位置訊號.............................................38
2.2回饋控制系統....................................................................40
2.2.1聽覺信號目標.................................................................40
2.2.2 感覺信號目標................................................................41
2.2.3運動區與感覺區的目標空間.........................................42
2.2.4 聽覺誤差和感覺誤差....................................................42
2.2.5運動區與誤差訊號.........................................................43
2.3前饋控制系統....................................................................43
第四章 實驗方法及設備..................................................................45
1聲調與基頻的關係......................................................................45
2 SPM統計繪圖器的操作及原理.................................................48
2.1 DIVA神經關聯..................................................................50
2.2模擬大腦活化....................................................................51
第五章 結果與討論..........................................................................53
1 結果.............................................................................................53
2 討論.............................................................................................59
第六章 未來展望..............................................................................63
1結論..............................................................................................63
2未來展望......................................................................................63
參考文獻...................................................................................................65
附錄Ａ SLT設定大腦功能區對應座標............................................68

                                

Ackermann, H., Riecker, A. (2004). "The contribution of the insula to motor aspects of speech production : A review and a hypothesis," Brain and Language, 89, 320-328.
Ackermann, H., Vogel, M., Petersen, D., Poremba, M. (1992). "Speech deficits in ischaemic cerebella lesions," Journal of Neurology, 239, 223-227.
Albe-Fessard, D. O. B. (1971). "Evoked cortical responses to vagal, laryngeal and facial afferents in monkeys under chloralose anaesthesia," J. H., Pimpaneau, A.,Electroencephalography and Clinical Neurophysiology, 31, 7-20.
Bohland, J. W., and Guenther, F. h. (2004). "An fMRI investigation of the neural bases of sequential organization for speech production," NeuroImage, 32, 821-841.
Browman , C. P. G. (1990). "Gestural specification using dynamically-defined articulatory structures," Journal of Phonetics, 18, 411-424
Callan, D. E. (1998). "An Auditory-Feedback-Based Model of Speech Production in the Developing Child," PHD. thesis, University of Wisconsin - Madison.
Dogil, G., Ackermann, H., Grodd, W., Haider, H., Kamo, H., Mayer, J., Riecker, A., Wildgruber, D. (2002). "The speaking brain: a tutorial introduction to fMRI experiment in the production of speech ,prosody and syntax," Journal of Neurolinguistic, 15, 59-90.
Edelman, G. M. (1987). Neural Darwinism : The Theory of Neuronal Group Selection. Basic Book, New York.
Fu, Q. J. Z. F. G.., Shannon, R. V., Soli, S.D. (1998). "Importance of tonal envelope cues in Chinese speech recognition," Journal of Acoustical Society of America, 104, 505-510.
Fujimura, O. (1994). "C/D Model : A Computational Model of Phonetic Implementation," Language Computations. Eric Sven Ristad ed., American Mathematical Society, U.S.A.
Guenther, F. H. (1994). "A neural network model of speech acquisition and motor equivalent speech production," Biological Cybernetics, 72, 43-53.
Howie, J. M. (1976). Acoustical studies of Mandarin vowels and tones. Cambridge University Press, Cambridge, UK.
Hsieh, L., Gandour, J., Wong, D., and Hutchins, G. D. (2000). "A PET study of the perception of Chinese tones," NeuroImage, 11, 5.
Kent, Ray D. (1992). The acoustic analysis of speech. Singular, London.
Ladefoged, P. (1963). " Some physiological parameters in speech," Language and Speech, 6, 109-119.
Lee, C.-Y., Tsai, J.-L., Kuo, W.-J., Yeh, T.-C., and Wu, Y.-T., Ho, L.-T., Hung, D. L., Tzeng, O. J., and Hsieh, J.-C. (2004). "Neuronal correlates consistency and frequency effects on Chinese character naming : an event-related fMRI study," NeuroImage, 23, 1235-1245.
Levelt, J. M. (1989). Speaking: From Intention to Articulation. MIT press, Cambridge Ma.
Liu, L., Peng, D., Ding , G., Jin, Z., Zhang , L., Li, K., and Chen, C. (2006). "Dissociation in the neural basis underlying Chinese tone and vowel production, " NeuroImage, 29, 515-523
Maeda, S. (1990). "Compensatory articulation during speech : Evidence from the analysis and synthesis of vocal-tract shape using an articulatory model," Speech production and Speech Modeling. 131-149, Kluwer Academic Publishers, The Netherlands.
Matin T. Hagan, Howard B. Demuth, Mark Beale (2004). 類神經網路設計. 湯姆生出版社, 台灣台北市。
Max, L., Guenther, F. H., Gracco, V. L., Ghosh, S. S., and Wallace, M. E. (2004). "Unstable or insufficiently activated internal models and feedback-biased motor control as sources of dysfluency: A theoretical model of stuttering," Contemporary Issues in Communication Science and Disorders, 31, 105-122.
Meyer, B. U., Werhahn, K., Rothwell, J. C., Roericht, S., and Fauth, C. (1994). "Functional organization of corticonuclear pathways to motoneurones of lower facial muscles in man," Experimental Brain Research, 101, 465-472.
Murphy, K., Corfield, D. R., Guz, A., Fink,G. R., Wise, R. J. S., Harrison, J., and Adams, L. (1997). "Cerebral areas associated with motor control of speech in human," J. Appl. Physiol, 83, 1438-1447.
Perkell, J., Matthies, M., Svirsky, M. A., and Jordan, M. I. (1993). "Trading relation between tongue-body raising and lip rounding in production of the vowel /u/ : a pilot motor equivalence study," Journal of the Acoustical Society of America, 93, 2948-2961.
Saltzman, E. L., and Munhall, K. G. (1989). "A dynamical approach to gestural patterning in speech production " Ecological Psychology, 1, 333-382.
Schroeder, C. E., and Foxe, J. J. (2002). "The timing and laminar profile of converging inputs to multisensory areas of the macaque neocortex," Brain Research.Cognitive Brain Research, 14, 187-198.
Tseng, C.-Y. (1990). An Acoustic Phonetic Study on Tones in Mandarin Chinese. Institute of History & Philology Academia Sinica, Special Publications No. 94. Taipei Taiwan.
Whalen, D. H., and Xu, Y. (1992). "Information for Mandarin tones in the amplitude contour and in brief segments," Phonetica, 49, 25-47.
Wise, R. J. S., Greene, J., Buchel, C., Scott, S. K. (1999). "Brain regions involved in articulation," Lancet, 353, 1057-1061.
林曉銘 (2004). "以嵌入式數位信號處理器發展中文語音合成系統
　　研究," 碩士論文, 中原大學電機工程學系。
鄭靜宜 (2004), “語音單調化對國語詞與和句子的辨識及語音清晰
度的影響,” 南師學報, 38, 175-196.
周鵬 (2004). 類神經網路入門, 全華出版社, 台灣台北市。
林依璇 (2007). "中文發生之神經相關聯性的腦功能磁振造影研究,
　　碩士論文, 國立中央大學電機工程學系。
羅華強 (2008). 類神經網路 : MATLAB的應用. 清蔚科技出版社, 台
　　灣新竹。
黃華民 (2008). 臨床神經解剖學基礎, 合記書局, 台灣台北。

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