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音乐教育中人工智能的运用 Music Education [13]

论文作者:www.51lunwen.org论文属性:硕士毕业论文 thesis登出时间:2014-07-07编辑:felicia点击率:24825

论文字数:8929论文编号:org201407062205435872语种:英语 English地区:中国价格:免费论文

关键词:principal approachesMusic EducationArtificial Intelligencecreativityproblem-seekingproblem-solving

摘要:音乐教育,是一个急需创造力、想象力、求知欲的教育领域,涉及到各个学科的知识内容,如音乐心理学、哲学、计算机科学等,随着音乐教育的不断发展,人工智能渐渐融入到音乐教育中。本文通过人工智能在音乐教育中的作用,探索其今后的发展。

ociate a logic program with each kind of constraints (sic) and to provide a generator of values for the variables.”


PLANC provides default values of variables of any plan for such generators. Beginners are then free to experiment with the elements of a plan. This allows exploration of possible effects regardless whether the student has extensive knowledge of the elements or not. Interaction between constraints and the default value generators is such that the defaults selected are very widely varied between specifications. The student is permitted to work bottom up or top down by the planner.


This means that when generating sequences, it is possible to specify low level matters and leave high level choices until later, and vice versa. This reflects the varied ways in which composers seem to like to work (Sloboda 1985). MC provides a suitable infrastructure for a wide range of teaching strategies appropriate to problem seeking domains (Holland 1989). However, an understanding of how MC components interact requires focus on one of the simplest, open-ended, user-directed learning strategies that MC supports.


6.1.4 Analysis by recomposition

One of way of using the system is to use an interesting piece and allow the student to ‘recompose’ it in a variety of ways. This is very beneficial for beginners. Each piece is linked to one or more harmonic plans and a variety of specification for each plan, which generates the piece. An analysis on each piece is provided from these plans. By selecting a viewpoint and making a limited number of changes to the specifications the user can recompose and re-generating the piece.


The new result may correspond with an existing piece in the body which the system can check and make remarks on or to a new piece. Changing the levels of strategies used via re-composition provides a step to exploring the nearby neighbours of the plan trees. The piece may be seen to have different nearby neighbours depending on the viewpoint chosen. The object of the exercise is not to harvest the new pieces generated or to learn the harmonic plans.


More importantly, a musically rich context where the interaction of musical materials and existing pieces can be explored provided by the interplay of elements which include: the multiple viewpoints, the corpus, the styles, and the new pieces generated. The plan trees can be directed to gain a better understanding of songs, viewpoints or musical materials depending on the students preferred focus.


The links between each of these components allow composition and analysis of existing pieces to be entwined flexibly. One of the key principles behind MC frameworks is the meaning of musical materials is not focused upon in a particular way, but from a variety of ways depending on which way they are used in different existing pieces, as seen from different viewpoints. Possibly, one of the most fundamental uses of musical analysis is comparing similarities and differences between real pieces.


The three layers of knowledge in the planner (net of constraints, the generators, and procedural code fragments) interact and produce musically intelligent behaviour. Knowledge is recorded independently of any particular use. This allows repeated use论文英语论文网提供整理,提供论文代写英语论文代写代写论文代写英语论文代写留学生论文代写英文论文留学生论文代写相关核心关键词搜索。

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