Hugo Wolf drew the strands of form, rhythm, and other elements together to form tightly woven songs, each element of which can be traced to the text as its original inspiration. Truly this was a genius of romantic expression, who took the tools developed by his predecessors in song, tempered them with his own sensitive personality, and used them to the fullest in setting the meaning and the mood, as well as the words, of the poems he had chosen.

近幾年來，華語流行音樂的發展越來越多元，而大眾所接收到的資訊是流行音樂當中的組成元素”曲與詞”，兩者分別具有賦予人類感知的功能，使人能夠深刻體會音樂作品當中所表答的內容與意境。然而，作曲與作詞都是屬於專業的創作藝術，作詞者通常在填詞時，會先對樂曲當中的結構進行粗略的分析，找出整首曲子的曲式，而針對可以填詞的部份，再進行更細部的分析將詞填入最適當的位置。流行音樂當中，曲與詞存在著密不可分的關係，瞭解歌曲結構不僅能降低填詞的門檻，亦能夠明白曲子的骨架與脈絡;在音樂教育與音樂檢索方面亦有幫助。 本研究的目標為，使用者輸入流行音樂歌曲，系統會自動分析出曲子的『曲式結構』。方法主要分成三個部分，分別為主旋律擷取、歌句分段與音樂曲式結構擷取。首先，我們利用Support Vector Machine以學習之方式建立模型後，擷取出符號音樂中之主旋律。第二步驟我們以”歌句”為單位，對主旋律進行分段，對於分段之結果建構出Self-Similarity Matrix矩陣。最後再利用Non-Negative Matrix Factorization針對不同特徵值矩陣進行分解並建立第二層之Self-Similarity Matrix矩陣，以歧異度之方式找出曲式邊界。 我們針對分段方式對歌曲結構之影響進行分析與觀察。實驗數據顯示，事先將歌曲以歌句單位分段之效果較未分段佳，而歌句分段之評測結果F-Score為0.82;將音樂中以不同特徵值建構之自相似度矩進行Non-Negative Matrix Factorization後，另一空間中之基底特徵更能有效地分辨出不同的歌曲結構，其F-Score為0.71。 / Music structure analysis is helpful for music information retrieval, music education and alignment between lyrics and music. This thesis investigates the techniques of music structure analysis for Chinese popular music. Our work is to analyze music form automatically by three steps, main melody finding, sentence discovery, and music form discovery. First, we extract main melody based on learning from user-labeled sample using support vector machine. Then, the boundary of music sentence is detected by two-way classification using support vector machine. To discover the music form, the sentence-based Self-Similarity Matrix is constructed for each music feature. Non-negative Matrix Factorization is employed to extract the new features and to construct the second level Self-Similarity Matrix. The checkerboard kernel correlation is utilized to find music form boundaries on the second level Self-Similarity Matrix. Experiments on eighty Chinese popular music are performed for performance evaluation of the proposed approaches. For the main melody finding, our proposed learning-based approach is better than existing methods. The proposed approaches achieve 82% F-score for sentence discovery while 71% F-score for music form discovery.

We have many developmental theories contributing to our understanding of children as they meander steadfastly toward maturation. Yet, none have reported on how young children interpret the qualitative meaning and importance of their own music-making experiences. Music created by average, not prodigious, young children is perceived by adults as “play” music rather than “real” music. But do young children take the same view as adults? When Piaget speaks of the young child’s qualitatively unique view and experience of the world (Ginsberg & Opper, 1988), can we assume that his statement encompasses young children’s predispositions related to music-making? Music is understood to occur when people act intentionally to produce and organize sound into rhythm and form. The guiding questions for this study are, What evidence is there to show that, when following an adult music leader, young children can engage in authentic music-making behavior and produce identifiable musical structures that move beyond random sounds or ‘noise’? What evidence is there to show that children's music-making behavior develops according to developmental stages? trek This qualitative field study observed and videotaped over 100 children between 2 and 7 years old who chose to engage in music-making behavior in a socially-rich school environment during structured activities guided by an adult “music leader.” The data gathered from this study suggest that young children’s motivation to make music derive from predispositions unrelated to notions of cultural and artistic expression thereby differing from adult musical needs and are instead based on more primary responses to their own developmental needs and their social environment. Functioning as “music leader,” the PI appeared to serve as an indispensable interface for assuring authenticity in the children’s music-making at all stages of development. The older children did not introduce any novel behavior specifically related to making music. However, due to the progression of cognitive and social maturity across the range of ages, new extra-musical behavior (EMB) slowly emerged at each developmental stage always seeming to enrich the experience relative to a particular group.