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Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/32731
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Title: | 人聲分類之研究 Analysis and Classification of Human Sounds |
Authors: | 蘇以暄 Su, Yi-Syuan |
Contributors: | 廖文宏 Liao, Wen-Hung 蘇以暄 Su, Yi-Syuan |
Keywords: | 人聲分類 |
Date: | 2005 |
Issue Date: | 2009-09-17 14:09:26 (UTC+8) |
Abstract: | 本論文探討的內容主要關於人聲分類之研究。在第一個層次,我們將家庭環境中的聲音分為說話聲、人聲非說話聲以及環境音三種。為了達到此目標,我們尋找了許多特徵並找出合適的幾個作為參數。 在夜間睡眠研究的部份,我們希望可以將整晚的睡眠資料分為鼾聲與非鼾聲兩部份,針對鼾聲的部份再深入去探討是否有呼吸中止的情況產生。若受試者是在醫院或者專業睡眠實驗室收錄資料,則會有其他睡眠生理訊號可供分析。本論文試著找出鼾聲與振動、睡姿與睡眠階段的關係並有初步的成果。 In this thesis, we describe the classification of audio signals in a smart home environment and in all-night sleep studies. In a home environment, our objective is different from most audio scene analysis projects in that we are mainly concerned with the distinction of human and non-human sounds. Toward this goal, we identify appropriate features to be extracted from the audio files and discuss the rationale behind choosing a particular feature. In all-night sleep recording, we describe the classification of audio signals recorded in all-night sleep studies. Our objective is to separate the episodes into snoring sounds and non-snoring sounds. We perform further analysis of the extracted snoring sounds to check if the testee has apnea. With polysomnogram data, we detect the relationship between snoring sounds and other sleep signals such as snoring vibration, sleep stages and body position. |
Reference: | 【1】F. Dalmasso, R. Prota, “Snoring: analysis, measurement, clinical implications and applications”, Euro Respir J., 1996, pp. 146-159. 【2】 J. E. Osborne, E. Z. Osman, P. L. Hill, B. V. Lee, C. Sparkes, “A New Acoustic Method of Differentiating Palatal from Non-palatal Snoring”, Clin. Otolaryngol 24, Blackwell Science Ltd, 1999, pp 130-133. 【3】 Jean-Julien Aucouturier and F. Pachet, “Music similarity measures: What’s the use?”, Proc. Int. Symposium on Music Info. Retrieval. (ISMIR), Paris, France, 2002. 【4】Jané R, Solà-Soler J, Fiz JA, Morera J, “Automatic Detection of Snoring Signals: Validation with Simple Snores and OSAS Patients”, Proceedings of the 22nd Annual International Conference of the IEEE EMBS, IEEE EMBS, Chicago IL, July 23-28, 2000, pp. 3129-3131. 【5】K. Wilson K, R.A. Stoohs, T.F. Mulrooney, L.J. Johnson, C. Guilleminault, Z. Huang, “The Snoring Spectrogram: Acoustic Assessment of Snoring Sound Intensity in 1,139 Individuals Undergoing Polysomnography”, Chest, March 1, 1999, pp. 762 – 770. 【6】L. Lu, H.J. Zhang, Senior Member, IEEE, and H. Jiang, “Content Analysis for Audio Classification and Segmentation,” IEEE Transactions on Speech and Audio Processing, Vol. 10, October 2002, pp 504-516. 【7】M. F. McKinney and J. Breebaart, “Features for Audio and Music Classification,” ISMIR 2003, October 2003. 【8】N.C.Saunders, P. Tassone, G. Wood, A. Norris, M. Harries, B. Kotecha,”Is Acoustic Analysis of Snoring an Alternative to Sleep Nasendoscopy?”, Clin. Otolaryngol, 29, Blackwell Publishing Ltd, 2004, pp 242-246. 【9】R. Vertegaal, “Attentive User Interfaces,” Communications of the ACM, Vol. 46, NO. 3, March 2003. 【10】Z. Liu, J. Huang, Y. Wang, and T. Chen, “Audio Feature Extraction & Analysis for Scene Classification,” IEEE Signal Processing Society 1997 Workshop on Multimedia Signal Processing, June 1997. 【11】劉勝義,「臨床睡眠檢查學」,合記出版社, 民國93年10月 【12】台灣睡眠醫學學會 http://www.tssm.org.tw/ |
Description: | 碩士 國立政治大學 資訊科學學系 93753004 94 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0937530041 |
Data Type: | thesis |
Appears in Collections: | [資訊科學系] 學位論文
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