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节奏的距离模型

A Distance Model for Rhythms
课程网址: http://videolectures.net/icml08_paiement_dmr/  
主讲教师: Jean-François Paiment
开课单位: IDIAP研究所
开课时间: 2008-08-06
课程语种: 英语
中文简介:
事实证明,用传统的机器学习方法很难实现时间序列中的长期依赖性建模。考虑音乐数据时会出现此问题。在本文中,我们引入了一个基于子序列之间距离分布的节律模型。描述了在考虑简单节奏表示上的汉明距离时模型的具体实现。在两个不同的音乐数据库上,所提出的模型在条件预测精度方面始终优于标准的隐马尔可夫模型。
课程简介: Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce a model for rhythms based on the distributions of distances between subsequences. A specific implementation of the model when considering Hamming distances over a simple rhythm representation is described. The proposed model consistently outperforms a standard Hidden Markov Model in terms of conditional prediction accuracy on two different music databases.
关 键 词: 机器学习; 节律模型; 节律模型
课程来源: 视频讲座网
数据采集: 2023-03-13:chenjy
最后编审: 2023-05-11:chenjy
阅读次数: 18