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Markov source model for printed music decoding

机译:用于印刷音乐解码的马尔可夫源模型

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Abstract: This paper describes a Markov source model for a simple subset of printed music notation. The model is based on the Adobe Sonata music symbol set and a message language of our own design. Chord imaging is the most complex part of the model. Much of the complexity follows from a rule of music typography that requires the noteheads for adjacent pitches to be placed on opposite sides of the chord stem. This rule leads to a proliferation of cases for other typographic details such as dot placement. We describe the language of message strings accepted by the model and discuss some of the imaging issues associated with various aspects of the message language. We also point out some aspects of music notation that appear problematic for a finite-state representation. Development of the model was greatly facilitated by the duality between image synthesis and image decoding. Although our ultimate objective was a music image model for use in decoding, most of the development proceeded by using the evolving model for image synthesis, since it is computationally far less costly to image a message than to decode an image. !8
机译:摘要:本文描述了一个简单的印刷音乐符号子集的马尔可夫源模型。该模型基于Adobe Sonata音乐符号集和我们自己设计的消息语言。和弦成像是模型中最复杂的部分。大多数复杂性来自于音乐排版规则,该规则要求将相邻音高的音符头放置在和弦杆的相对两侧。此规则导致其他印刷细节(例如点放置)的情况激增。我们描述了模型接受的消息字符串的语言,并讨论了与消息语言各个方面相关的一些成像问题。我们还指出了音乐符号的某些方面对于有限状态表示来说是有问题的。图像合成和图像解码之间的双重性极大地促进了模型的开发。尽管我们的最终目标是用于解码的音乐图像模型,但是大多数开发都是通过使用演化模型进行图像合成来进行的,因为对消息进行成像比对图像进行解码在计算上要便宜得多。 !8

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