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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 應用力學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23339
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor邵耀華
dc.contributor.authorChou-Min Chiaen
dc.contributor.author賈澤民zh_TW
dc.date.accessioned2021-06-08T04:59:25Z-
dc.date.copyright2010-08-19
dc.date.issued2010
dc.date.submitted2010-08-18
dc.identifier.citation[1] Horii, Y. (1982). Some voice fundamental frequency characteristics of oral reading and spontaneous speech by hard-of-hearing young women. Journal of Speech & Hearing Research, 25, 608–610.
[2] Yumoto, E., Gould, W.J., & Baer, T. (1982): “Harmonics-to-noise ratio as an index of the degree of hoarseness”, Journal of the Acoustical Society of America 71: 1544-1550.
[3]Titze.I.R.(1989).On the relation between subglottal pressure and fundamental frequency in phonation. J. Acoust. Soc. Am,85(2).
[4] Zwirner, P., Murry, T., Woodson, G. E. (1991).Phonatory function of neurologically impaired patients.Journal of Communication Disorders, 24, 287–300.
[5]Titze, I. R. (1991).Amodel for neurologic sources of aperiodicity in vocal fold vibration. Journal of Speech & Hearing Research, 34, 460–472.
[6] Aronson, A. E., Ramig, L. O., Winholtz, W. S., Silber, S. R. (1992). Rapid voice tremor, or “flutter,” in amyotrophic lateral sclerosis. Annals of Otology, Rhinology&Laryngology, 101, 511–518
[7] Aronson, A. E., Ramig, L. O., Winholtz, W. S., Silber, S. R. (1992).Rapid voice tremor, or “flutter,” in amyotrophic lateral sclerosis.Annals of Otology, Rhinology&Laryngology, 101, 511–518.
[8] Hsiao, T. Y., Solomon, N. P., Luschei, E. S., Titze, I. R. (1994). Modulation of fundamental frequency by laryngeal muscles during vibrato.Journal of Voice, 8, 224–229.
[9] Jean Schoentgen, Raoul de Guchteneere(1995). Time series analysis of jitter. Journal of Phonetics (1995) ,23, 189-201.
[10]Orlikoff, R. F., Kraus, D. H., Harrison, L. B., Ho, M. L., Gartner, C. J. (1997). Vocal fundamental frequency measures as a reflection of tumor response to chemotherapy in patients with advanced laryngeal cancer. Journal of Voice, 11, 33–39.
[11]Huang, N. E., Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen,C. C. Tung, and H. H. Liu, 1998: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc.
R. Soc. London, Ser. A, 454, 903–995.
[12] Rothman, H. B., Brown, W. S.Jr, Sapienza, C. M., Morris, R. J. (2001). Acoustic analyses of trained singers perceptually identified from speaking samples. Journal of Voice, 15, 25–35.
[13] Alain de Cheveigne and Hideki Kawahara(2002).YIN, a fundamental frequency estimator for speech and music. J. Acoust. Soc. Am. 111 (4), April 2002
[14]Watts, C., Barnes-Burroughs, K., Andrianopoulos, M., Carr, M.(2003). Potential factors related to untrained singing talent: a survey of singing pedagogues. Journal of Voice, 17, 298–307.
[15]Leydon, C., Bauer, J. J., Larson, C. R. (2003). The role of auditory feedback in sustaining vocal vibrato.Journal of the AcousticalSociety of America, 114, 1575–1581.
[16] Jinfu Ni, Keikichi Hirose,2006, Quantitative and structural modeling of voice fundamental frequency contours of speech in Mandarin, Journal of Speech Communication 48,989–1008.
[17]Guo-She Lee, Tzu-Yu Hsiao, Cheryl C. H. Yang, and Terry B. J. Kuo(2007). Effects of Speech Noise on Vocal Fundamental Frequency Using Power Spectral Analysis. Ear & Hearing 2007;28;343–350.
[18] Meike Brockmann, Michael J. Drinnan, Claudio Storck, and Paul N. Carding, 2009, Reliable Jitter and Shimmer Measurements in Voice Clinics: The Relevance of Vowel, Gender, Vocal Intensity, and Fundamental Frequency Effects in a Typical Clinical Task, Journal of Voice
[19]Frequency Analysis,1977,R. B. Randall, B. Tech.,B. A
[20]蒙以正,2004,數位信號處理:應用MATLAB
[21] 林其盛,2008,數值分析基礎篇
[22]蕭自佑,1999,音聲醫學概論
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23339-
dc.description.abstract音聲的品質,主要決定於聲帶振動所產生的聲波。此聲波的規律性,也就是音聲基頻的穩定性,關係著音聲品質的好壞。因此分析音聲基頻的穩定性,即可對音聲品質做出適當的評估。以往對於分析音聲基頻變異的方式主要以抖動(Jitter)分析為主,但是抖動分析僅能提供音聲基頻變異量的程度並無法提供基頻訊號之變異頻率及功率分佈,使評估者無法明確的辨別音聲基頻變異的原因。因此本研究在此設計一新的分析音聲基頻變異法,藉由傅立葉及希爾伯特-黃轉換法提供基頻訊號的變異頻率範圍及功率分佈,以這些參數做為音聲品質的量化指標,以彌補抖動分析的不足。本研究找了40位音聲品質正常的受試者,共有20位男性及20位女性;6位音聲品質異常的病患,共2位男性,4位女性,被用來評估所提出的分析流程之效能。由實驗結果得知,對於聲帶振動體的材料及幾何特性不規則的病患而言,音聲基頻訊號確實會在10~25Hz的頻率範圍有異常的功率產生。
另外本實驗的結果亦顯示,單以音聲基頻的穩定性做為評估音聲品質的指標似乎是不足的。
zh_TW
dc.description.abstractVoice quality is determined by the regularity of the wave produced by the vocal folds, which also represents the regularity of the voice fundamental frequency. Analyzing voice fundamental frequency stability can therefore be a proper assessment of voice quality. Jitter analysis used to measure voice fundamental frequency stability has been for decades, but jitter analysis can only provide the voice fundamental frequency variation being normal or not. It cannot reveal the variation frequency and the variation power distribution, the measurement of jitter may have difficulties on evaluating the disease severity. Therefore, in this study a new method of analyzing voice fundamental frequency variation by Fourier and Hilbert - Huang Transform was designed. It provided the measurement of variation frequency and power distribution of the voice fundamental frequency signal. Forty subjects with normal voice quality, twenty males and twenty females; six patients with dysphonia, two males and four females, were studied. The results indicated that, hoarse voice signals had fundamental frequency with larger 10~25Hz variation power than normal voice. Additionally, evaluation voice quality only by voice fundamental frequency variation seems to be insufficient for describing the severity of dysphonia.en
dc.description.provenanceMade available in DSpace on 2021-06-08T04:59:25Z (GMT). No. of bitstreams: 1
ntu-99-R97543065-1.pdf: 1941795 bytes, checksum: a49a7a7ee1b17e5b97c93af0176c4348 (MD5)
Previous issue date: 2010
en
dc.description.tableofcontents口試委員會審定書 i
致謝 ii
中文摘要 iii
英文摘要 iv
第一章緒論 1
1-1前言 1
1-2 文獻回顧 2
1-3 研究動機與目的 5
第二章聲帶結構簡介 7
2-1 喉部的解剖說明 7
2-2 聲帶的顯微構造 8
2-3喉部肌肉對聲帶的調整作用 9
2-4 聲帶的振動 10
第三章訊號分析理論簡介 13
3-1聲帶振動特性分析 13
3-1-1修正差函數法(Modify Difference Function) 13
3-2基頻軌跡擬合 14
3-2-1牛頓均差法(Newton`s divided differences) 14
3-2-2樣條函數均差法(spline) 16
3-2-3最小平方法(Least square) 18
3-2-4 對數函數法(Logarithmic Function) 21
3-3基頻訊號之頻譜分析 23
3-4 希爾伯特-黃轉換(Hilbert-Huang Transform) 25
第四章實驗設計及流程簡介 29
4-1研究對象: 29
4-2硬體及軟體設置: 29
4-3音聲訊號分析流程: 30
4-4實驗設計: 32
4-4-1曲線擬合方法校正設計 32
4-4-2正常人平均功率分佈範圍 34
第五章實驗結果與討論 37
5-1曲線擬合方法校正結果 37
5-1-1頻譜分析法 37
5-1-2希爾伯特-黃分析法 38
5-2正常人平均功率分佈範圍結果 39
5-2-1頻譜分析法 39
5-2-2希爾伯特-黃分析法 41
5-3結果討論 42
第六章結論及後續研究 45
第七章參考資料 47
附錄一 74
附錄二 77
表 目 錄
表4-1 鋼琴鍵音調名稱及其基本頻率關係表 51
表5-1 相關係數(Correlation Coefficient)分析結果(頻譜分析) 52
表5-2相關係數(Correlation Coefficient)分析結果(希爾伯特-黃分析法) 54
圖 目 錄
圖2-1喉部的結構(蕭自佑,1999) 55
圖2-2喉部的骨架(蕭自佑,1999) 55
圖2-3聲帶的顯微構造(蕭自佑,1999) 55
圖2-4環甲肌的作用(Tucker,1987) 56
圖2-5甲杓肌的作用(Tucker,1987) 56
圖2-6側環杓肌的作用(Tucker,1987) 56
圖2-7後環杓肌的作用(Tucker,1987) 57
圖2-8杓間肌的作用(Tucker,1987) 57
圖2-9發聲時之氣體動力學曲線(Titze,1988) 57
圖3-1原始聲壓訊號 58
圖3-2原始和平移訊號關係圖 58
圖3-3修正差函數圖 58
圖3-4原始基頻訊號 59
圖3-5Runge現象 59
圖3-6牛頓均差法 59
圖3-7原始基頻訊號 60
圖3-8三次漾條內插法 60
圖3-9相容方程組 60
圖3-10不相容方程組 61
圖3-11最小平方法 61
圖3-12對數函數法 61
圖4-1分析窗值(window) 62
圖4-2平移T秒後之窗值(window) 62
圖4-3離散非等區間即時基頻訊號 62
圖4-4即時音分(cent)圖 63
圖4-5(a)牛頓均差擬法 63
圖4-5(b)樣條函數法 63
圖4-5(c)最小平方法 64
圖4-5(d)對數函數法 64
圖4-6基頻變異功率譜密度圖 64
圖4-7基頻變異模態圖 65
圖5-1正常男性最小平方法頻譜功率分布範圍 66
圖5-2正常女性最小平方法頻譜功率分布範圍 66
圖5-3正常男性對數函數法頻譜功率分布範圍 67
圖5-4正常女性對數函數法頻譜功率分布範圍 67
圖5-5男性病患最小平方法頻譜功率圍 68
圖5-6男性病患對數函數法頻譜功率圍 68
圖5-7 女性病患最小平方法頻譜功率圍 69
圖5-8 女性病患對數函數法頻譜功率圍 69
圖5-9正常男性最小平方法模態功率分布範圍 70
圖5-10正常女性最小平方法模態功率分布範圍 70
圖5-11正常男性對數函數法模態功率分布範圍 71
圖5-12正常女性對數函數法模態功率分布範圍 71
圖5-13男性病患最小平方法模態功率圍 72
圖5-14男性病患對數函數法模態功率圍 72
圖5-15女性病患最小平方法模態功率圍 73
圖5-16女性病患對數函數法模態功率圍 73
附錄一 74
附錄二 77
dc.language.isozh-TW
dc.title分析音聲基頻變異方法之研究zh_TW
dc.titleThe methods of analyzing the voice fundamental frequency variationen
dc.typeThesis
dc.date.schoolyear98-2
dc.description.degree碩士
dc.contributor.coadvisor蕭自佑
dc.contributor.oralexamcommittee王崇禮,張家歐
dc.subject.keyword音聲基頻,音聲品質,抖動分析,功率譜密度,希爾伯特-黃轉換,zh_TW
dc.subject.keywordvoice fundamental frequency,voice quality,jitter analysis,power spectral density,Hilbert -Huang transform,en
dc.relation.page86
dc.rights.note未授權
dc.date.accepted2010-08-19
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept應用力學研究所zh_TW
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