在日常生活中，我們每天都會透過聲音來與人溝通，然而，隨著年紀漸長或其他疾病引起的聲帶異常疾病，往往使人無法正常發聲而前往耳鼻喉科門診求診。在門診中，多數聲帶異常疾病皆會造成聲帶閉合不全的問題，而解決這類問題最常見的治療方式就是聲帶脂肪注射手術(lipoinjection thyroplasty)。 雖然大部分的患者經手術治療後都能恢復正常的嗓音，但對部分患者而言，因為脂肪會被吸收而需要作重複注射(re-injection)或聲帶內移手術(Medialization surgery)。一般在醫院裡除了使用內視鏡等醫療儀器作檢測外，也會用多向度嗓音分析儀(MDVP)對患者之錄音檔作分析，以此判斷手術成效。然而，比起用錄音檔來分析，若能直接對發聲端－聲帶產生的波形作分析，或許可以更精準地評估手術成效。
在本論文中，我們利用線性預估方法(Linear Prediction)求出模擬聲帶端波形的預估誤差波形(Prediction Error)，在設定的振幅範圍內，計算預估波形每音框平均通過的波峰數作為新的聲音指標，以此評估手術成效。我們收集17位進行聲帶脂肪注射手術的患者資料，其中9位為手術成功組，其餘8位為手術失敗組。我們將所有患者之手術前、手術後一個月以及手術後三個月錄音檔作新聲音指標分析，發現手術失敗組與成功組的指標結果呈現不同的趨勢，並以ROC曲線下面積(AUC)作其分辨力的評估，確實可區別手術失敗組與成功組至一定程度(AUC>0.7)。
在未來，期盼能收集更多患者資料進行分析，並將此指標實際應用於醫療上，及早為患者安排最適當的治療規劃，並節省其診療時間及不必要的花費。

摘要 I
Abstract II
致謝 IV
目次 V
第一章 緒論 1
1.1 研究動機與目的 1
1.2 研究內容 2
1.3 章節大綱 2
第二章 人體發音構造與聲帶疾病檢測及治療方式 3
2.1 人體發音的構造 3
2.1.1 聲帶的基本構造 5
2.1.2 聲帶相關疾病及治療方式 6
2.1.3 自體脂肪注射手術介紹 7
2.2 多向度嗓音分析儀及其在醫學上的應用 8
2.2.1 多向度嗓音分析儀 8
2.2.2 醫學上常用的音聲指標[20] 11
第三章 系統架構原理 13
3.1 聲帶端激發訊號之聲學模型[3] 13
3.2 線性預估分析 16
3.2.1 發音模型[3] 16
3.2.2 線性預估模型[3][26] 20
3.2.3 線性預估係數求法[3] 22
第四章 實驗方法與結果討論 24
4.1 實驗流程及方法 24
4.2 多向度嗓音分析儀分析結果 32
4.3 新指標參數之分析結果 36
4.4 ROC曲線下之面積分析 38
4.5 問題與討論 44
第五章 結論與未來展望 46
5.1 結論 46
5.2 未來展望 47
參考文獻 48

[1] E. Yumoto, W. J. Gould, and T. Baer, “Harmonics-to-noise ratio as an index of the degree of hoarseness,” The Journal of the Acoustical Society of America, vol. 71, no. 6. pp. 1544–1549, Jun. 1982.
[2] D. G. Silva, L. C. Oliveira, and M. Andrea, “Jitter estimation algorithms for detection of pathological voices,” EURASIP Journal on Advances in Signal Processing, vol. 2009, no. 9, p.1-9, 2009.
[3] 王小川, 語音訊號處理(修訂二版), 全華圖書, 台北縣土城市, 2009.
[4] L. Rabiner, B. H. Juang., Foundamentals of speech recognition. Prentice-Hall, Inc., 1993, pp. 30–33.
[5] J. H. Brandenburg, W. Kirkham, and D. Koschkee, “Vocal cord augmentation with autogenous fat,” The Laryngoscope, vol. 102, no. 5, pp. 495–500, 1992.
[6] D. O. Mikaelian, L. D. Lowry, and R. T. Sataloff, “Lipoinjection for unilateral vocal cord paralysis,” The Laryngoscope, vol. 101, no. 5, pp. 465–468, 1991.
[7] H. Umeno et al.,“Analysis of voice function following autologous fat injection for vocal fold paralysis,” Otolaryngology--head and neck surgery, vol. 132, no. 1, pp. 103–107, Jan. 2005.
[8] T. M. McCulloch et al., “Long-term follow-up of fat injection laryngoplasty for unilateral vocal cord paralysis,” The Laryngoscope, vol. 112, no. 7, pp. 1235–1238, 2002.
[9] O. Laccourreye et al., “Intracordal injection of autologous fat in patients with unilateral laryngeal nerve paralysis: long-term results from the patient’s perspective,” The Laryngoscope, vol. 113, no. 3, pp. 541–545, 2003.
[10] M. W. Hsiung et al., “Fat augmentation for glottic insufficiency,” The Laryngoscope, vol. 110, no. 6, pp. 1026–33, Jun. 2000.
[11] B. S. Kim et al., “Usefulness of laryngeal phonation CT in the diagnosis of vocal cord paralysis,” American journal of roentgenology, vol. 190, no. 5, pp. 1376–1379, May 2008.
[12] R. Schwarz et al., “Classification of unilateral vocal fold paralysis by endoscopic digital high-speed recordings and inversion of a biomechanical model,” IEEE transactions on bio-medical engineering, vol. 53, no. 6, pp. 1099–1108, Jun. 2006.
[13] P. C. Belafsky et al., “Muscle tension dysphonia as a sign of underlying glottal insufficiency,” Otolaryngology--head and neck surgery, vol. 127, no. 5, pp. 448–451, Nov. 2002.
[14] D. D. Deliyski, “Acoustic model and evaluation of pathological voice production,” in Third European Conference on Speech Communication and Technology, 1993, pp. 1969–1972.
[15] R. D. Kent et al., “Voice dysfunction in dysarthria: application of the Multi-Dimensional Voice ProgramTM,” Journal of Communication Disorders, vol. 36, no. 4, pp. 281–306, Jul. 2003.
[16] G. Cantarella et al., “Outcomes of structural fat grafting for paralytic and non-paralytic dysphonia,” Acta otorhinolaryngologica Italica, vol. 31, no. 3, pp. 154–160, Jun. 2011.
[17] J. B. Jensen, N. Rasmussen, “Phonosurgery of vocal fold polyps, cysts and nodules is beneficial,” Danish medical journal, vol. 60, no. 2, p.1-5, Feb. 2013.
[18] S. Zelcer et al., “Multidimensional voice program analysis (MDVP) and the diagnosis of pediatric vocal cord dysfunction,” Annals of Allergy, Asthma & Immunology, vol. 88, no. 6, pp. 601–608, 2002.
[19] KayPentax, “Disordered voice database and program, model 4337” [Online]. Available: http://www.kayelemetrics.com/index.php?option=com_product&Itemid=3&controller=product&task=learn_more&cid[]=52.
[20] KayPentax, Software instruction manual: Multi-Dimensional Voice Program(MDVP) Model 5105, KayPentax, 2008.
[21] J. Makhoul, “Linear prediction: a tutorial review,” Proceedings of the IEEE, vol. 63, no. 4, 1975.
[22] G. U. Yule, “On a method of investigating periodicities in disturbed series, with special reference to Wolfer’s sunspot numbers,” Philosophical Transactions of the Royal Society, vol. 226, pp. 267–298, 1927.
[23] D. Y. Wong, J. D. Markel, “An excitation function for LPC synthesis which retains the human glottal phase characteristics,” IEEE Int. Conf. Acoust., Speech, Signal Processing, 1978, pp. 171–174.
[24] H. W. Strube, “Determination of the instant of glottal closure from the speech wave,” The Journal of the Acoustical Society of America, vol. 56, no. 5, pp. 1625–9, Nov. 1974.
[25] A. B. M. S. U. Doulah, Islam S., “Detection of various diseases by using formant track extraction and pitch contour analysis,” in Proceedings of 14th International Conference on Computer and Infonnation Technology, 2011.
[26] L. R. Rabiner, R. W. Schafer, “Introduction to digital speech processing,” Foundations and Trends in Signal Processing, vol. 1, no. 1–2, pp. 1–194, 2007.
[27] T. Drugman et al., “Detection of glottal closure instants from speech signals : a quantitative review,” vol. 20, no. 3, pp. 994–1006, 2012.
[28] R. Jang, “Audio signal processing and recognition” [Online]. Available: http://neural.cs.nthu.edu.tw/jang/books/audiosignalprocessing/index.asp.
[29] U. G. Goldstein, “An articulatory model for the vocal tracts of growing children,” D. Sc. thesis , Massachusetts Institute of Technology, 1980.
[30] E. Billauer., “peakdet: Peak detection using MATLAB” [Online]. Available: http://www.billauer.co.il/peakdet.html.
[31] T. Fawcett, “An introduction to ROC analysis,” Pattern Recognition Letters, vol. 27, no. 8, pp. 861–874, Jun. 2006.
[32] T. B. Newman, M. A. Kohn, Evidence-Based Diagnosis, Cambridge University Press, 2009.
[33] A. E. Bradley, “The use of the area under the ROC curve in the evaluation of machine learning algorithms,” Pattern Recognition, vol. 30, no. 7, pp. 1145–1159, 1997.
[34] J. A. Hanley, B. J. McNeil, “The meaning and use of the area under a receiver operating characteristic (ROC) curve,” Radiology, vol. 143, no. 1, pp. 29–36, 1982.
[35] T. G. Tape, “The area under an ROC curve” [Online]. Available: http://gim.unmc.edu/dxtests/roc3.htm.