請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43432完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭士康(Shyh-Kang Jeng) | |
| dc.contributor.author | Yen-Ting Chen | en |
| dc.contributor.author | 陳彥廷 | zh_TW |
| dc.date.accessioned | 2021-06-15T01:56:31Z | - |
| dc.date.available | 2010-08-14 | |
| dc.date.copyright | 2009-08-14 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2009-06-26 | |
| dc.identifier.citation | [1] J. Biles, “GenJam: A Genetic Algorithm for Generating Jazz Solos,” in International Computer Music Conference, 1994, pp. 131-131.
[2] M. Hamanaka, M. Goto, and N. Otsu, 'Learning-Based Jam Session System for a Guitar Trio,' 6, 2001, p. 7. [3] M. Goto, I. Hidaka, H. Matsumoto et al., 'A Jazz Session System for Interplay Among All Players - VirJa Session (Virtual Jazz Session System) -.' pp. 346-349, 1996. [4] I. Hidaka, M. Goto, and Y. Muraoka, 'An Automatic Jazz Accompaniment System Reacting to Solo.' pp. 167-70, 1995. [5] Band-in-a-Box, 1990. [6] C. L. Lu, “An Interactive Jazz Piano Accompaniment System,” Master, Graduate Institute of Communication Engineering, National Taiwan University, 2009. [7] L. Rabiner, and B. Juang, “An Introduction to Hidden Markov Models,” ASSP Magazine, IEEE, vol. 3, no. 1 Part 1, pp. 4-16, 1986. [8] L. R. Rabiner, 'A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition.' pp. 257-286, 1989. [9] J. E. Berendt, G. Huesmann, H. Bredigkeit et al., The Jazz book: from Ragtime to Fusion and Beyond: Lawrence Hill Books, 1992. [10] C. Sher, B. Bauer, and L. Dunlap, The New Real Book. Volume 3: Sher Music. [11] B. Nettles, Harmony I, Fall 2001 ed., 1987. [12] S. Pellman, An Introduction to the Creation of Electroacoustic Music: Wadsworth Pub. Co., 1994. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43432 | - |
| dc.description.abstract | iComper是一能理解演奏者即興時所傳達的意圖之互動爵士伴奏系統。在本論文中，我們提出一個基於隱馬可夫模型之音樂信號偵測機制，透過這個機制橋接伴奏者在聆聽音樂時，透過所學之音樂理論及聆聽感受得到的理解與即興者演奏時傳達出的意圖。我們將即興者演奏的旋律以音樂理論為基礎之特徵擷取方法取出資訊並對應至觀察現象之代號。偵測機制會使用從樂曲開始到現下小節的觀察現象序列給予最可能的狀態。透過本文提出的鼓節奏產生演算法，組合從資料庫中取出的打擊樂器樣本以及音量變化樣本得到打擊樂器之伴奏。 | zh_TW |
| dc.description.abstract | iComper (interactive Comper) is an interactive Jazz accompaniment system which understands various soloist's intention when he or she improvises. In this thesis, we propose an HMM-based musical sign detector to bridge accompanist's realization when listening to music and intention given by the improviser. We apply music theory to our feature extractors on improviser's melody and map features to observations. The detector gives the highest-probability state using the observation sequence from the start of a tune to the current measure. A re-drum algorithm is proposed to combine the chosen percussion patterns and the volume pattern to generate accompaniment. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T01:56:31Z (GMT). No. of bitstreams: 1 ntu-97-R96944009-1.pdf: 593457 bytes, checksum: 02dd5074d794f93cb1541b43b1ec32a4 (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | 誌謝 i
Abstract ii 摘要 iii CONTENTS iv LISTS OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Literature Survey 2 1.3 Goal of Thesis 3 1.4 Organization of Thesis 3 Chapter 2 Background 4 2.1 Hidden Markov Model 4 2.2 Playing a Jazz Tune 5 2.3 Tension 7 2.4 MIDI 8 Chapter 3 iComper System Overview 10 3.1 System Architecture 10 3.2 Components of iComper 12 3.2.1 Melody Transformer 12 3.2.2 Feature Extraction 12 3.2.3 HMM-based Musical Sign Detector 13 3.2.4 Re-Drum Algorithm 13 3.3 Modes of iComper 14 3.3.1 Learning Mode 14 3.3.2 Performing Mode 15 Chapter 4 HMM-based Musical Sign Detector 17 4.1 Design of Musical Sign Detector 17 4.2Pre-processing 18 4.2.1 Feature Extraction 19 4.2.2 Features/Symbol Map 21 4.3 Hidden Markov Model 22 Chapter 5 Re-Drum Algorithm 24 5.1 Design of Re-Drum Algorithm 24 5.2 Pre-processing 24 5.2.1 Onset Vector 25 5.2.2 Volume Ratio Vector 26 5.3 Re-Drum 26 5.3.1 Volume Pattern Selection 27 5.3.2 Percussion Pattern Selection 28 5.3.3 Percussion Generation 29 Chapter 6 Experiments and Discussions 31 6.1 Training the Probability Model 31 6.2 Testing Result of HMM-based Musical Sign Detector 33 6.3 Evaluation 37 6.4 Questionnaire 39 Chapter 7 Conclusions 43 Appendix A Score of Autumn Leaves 44 Appendix B MIDI Note Number Table 45 Reference 46 | |
| dc.language.iso | en | |
| dc.subject | 伴奏 | zh_TW |
| dc.subject | 互動 | zh_TW |
| dc.subject | 隱馬可夫 | zh_TW |
| dc.subject | 鼓 | zh_TW |
| dc.subject | 爵士 | zh_TW |
| dc.subject | drum | en |
| dc.subject | HMM | en |
| dc.subject | interactive | en |
| dc.subject | accompaniment | en |
| dc.subject | jazz | en |
| dc.title | iComper:使用隱馬可夫模型於偵測音樂暗示之互動鼓手 | zh_TW |
| dc.title | iComper: An Interactive Drummer using HMM-based Musical Sign Detector | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 張智星(Jyh-Shing Roger Jang),蘇文鈺(Alvin Su),黃乾綱(Chien-Kang Huang) | |
| dc.subject.keyword | 互動,隱馬可夫,鼓,爵士,伴奏, | zh_TW |
| dc.subject.keyword | interactive,HMM,drum,jazz,accompaniment, | en |
| dc.relation.page | 46 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-06-29 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
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