Real-Time Audio-to-Score Alignment of Music Performances Containing Errors and Arbitrary Repeats and Skips
Real-Time Audio-to-Score Alignment of Music Performances Containing Errors and Arbitrary Repeats and Skips
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DOI：
10.1109/taslp.2015.2507862
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
Tomohiko Nakamura;Eita Nakamura;S. Sagayama
中科院分区：
文献类型：
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作者：
Tomohiko Nakamura;Eita Nakamura;S. Sagayama
本文讨论了音乐表演的音频信号与相应的乐谱（a.k.a.乐谱跟随），其可以处理演奏中的克里思变化、错误和任意重复和/或跳过（重复/跳过）。这种类型的乐谱跟随在练习和排练的自动伴奏中特别有用，其中经常出现错误和重复/跳过。简单的扩展以前在文献中提出的算法是不适用于在这些情况下的分数的实际长度，由于大的计算复杂性的问题。为了科普这个问题，我们提出了两个隐马尔可夫模型的单声道性能的错误和任意重复/跳过，并推导出有效的分数以下的算法与假设之前和之后的重复/跳过的分数位置的先验概率分布是相互独立的。我们证实了实时操作的算法与乐谱的实际长度（约10000个音符）在现代笔记本电脑和他们的跟踪能力，平均在0.7秒内的输入性能后，重复/跳过单簧管性能数据。本文还讨论了对复音信号的进一步改进和扩展。
This paper discusses real-time alignment of audio signals of music performance to the corresponding score (a.k.a. score following) which can handle tempo changes, errors and arbitrary repeats and/or skips (repeats/skips) in performances. This type of score following is particularly useful in automatic accompaniment for practices and rehearsals, where errors and repeats/skips are often made. Simple extensions of the algorithms previously proposed in the literature are not applicable in these situations for scores of practical length due to the problem of large computational complexity. To cope with this problem, we present two hidden Markov models of monophonic performance with errors and arbitrary repeats/skips, and derive efficient score-following algorithms with an assumption that the prior probability distributions of score positions before and after repeats/skips are independent from each other. We confirmed real-time operation of the algorithms with music scores of practical length (around 10000 notes) on a modern laptop and their tracking ability to the input performance within 0.7 s on average after repeats/skips in clarinet performance data. Further improvements and extension for polyphonic signals are also discussed.