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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Style Music Accompaniment Using a Variable-length Genetic Algorithm with Chord Progression

Chou, Yan-Chi 10 September 2009 (has links)
The domain of computer music is an interesting area which combines computer science and music art. We propose a music accompaniment system using a variable-length genetic algorithm. Via the system one can make the music corresponded to his demands. In the style music accompaniment we analyze some important characteristic of pop music, and propose a new chromosome representation scheme to include the concept of rhyme, chord and melody. Chord progression is used as one of the evaluation criterions in this thesis. The system allows a user to input melody, to select emotion and rhyme, and the system will automatically generate the appropriate accompaniment based on the database compiled from some music theory relating to the chord progression. In addition, the system allows a user to select his favorite accompaniment that generated by the system. Based on the user selected accompaniment the system will generate similar accompaniments for the user.
2

流行音樂組曲之電腦音樂編曲 / Computer Music Arrangement for Popular Music Medley

董信宗, Tung,Hsing-Tsung Unknown Date (has links)
在音樂中,組曲是一種特別的創作形式。組曲將多首音樂段落組合排列,並且在音樂段落之間加入間奏,形成一首音樂組曲。組曲的編曲重點在於音樂段落的編排順序及段落之間的連結。平時在宴會、舞會、餐廳、賣場等場合中,往往都會連續播放多首流行音樂。利用電腦編曲自動產生流行音樂組曲,將可提升播放音樂的銜接與流暢感。 因此,本研究利用資料探勘技術及音樂編曲理論,將多首音樂重新改編成一首組曲。系統首先將每首音樂分段並找出每首音樂的代表段落。接著,系統根據代表段落間的相似度編排順序。最後,為了達到組曲中音樂段落連接的流暢性,我們以模型訓練的方式在段落連結間加入間奏。系統從訓練資料學習產生旋律發展、和弦進程與節奏的模型,接著分析代表段落的動機、旋律、和弦及節奏,使得組曲編曲後的段落連結更為流暢且完整。本研究以流行音樂鋼琴伴奏曲為測試資料,我們分別邀請三十四位受過音樂訓練與未受音樂訓練的測試者,針對本研究所提出的鋼琴伴奏節奏辨識、代表段落萃取、段落順序編排及間奏產生,評估其效果。實驗結果顯示,本研究所提出的順序編排與間奏產生技術,對於組曲的流暢感,有著相當大的幫助。 / In music, a medley is an organized piece composed from segments of existing pieces. Ordering and bridge for connection between segments are the important elements for medley arrangement. Automatic medley arrangement is helpful for playing a set of music continuously which is common in banquet, party, restaurant, shopping mall, etc.. This thesis aims to develop the automatic medley arrangement method by using data mining techniques and music arrangement theory. The proposed method first segments each music and discovers the significant segment from each music. Then, the linear arrangement based on the similarities between significant segments is generated. Finally, in order to connect segments smoothly in the medley, the bridge between two segments is generated and inserted by using model training. Three models, melody progression, chord progression and rhythm models are learned from training data. For the experiments, testing data is collected from popular piano music and thirty-four people are invited to evaluate the effectiveness of the rhythm recognition of accompaniment, the extraction of significant segment, the linear arrangement of segments, and the creation of bridge. Experimental results show that the proposed medley arrangement method performs well.

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