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Model for memory-based music transcription and its Variational Bayes solution

机译:基于记忆的音乐转录模型及其变分贝叶斯解决方案

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摘要

The problem of memory based music transcription is considered and a probabilistic model for polyphonic music is proposed. Parameters of the model correspond to labels of the pre-recorded sounds and their amplitudes. Since exact estimation of the parameters is computationally prohibitive, we develop an approximate estimation algorithm using the Variational Bayes approximation. Results of the proposed algorithm are compared to alternative algorithms on piano recordings.
机译:考虑了基于记忆的音乐转录问题,并提出了复音音乐的概率模型。模型的参数对应于预先记录的声音的标签及其振幅。由于参数的精确估计在计算上是不允许的,因此我们使用变分贝叶斯近似来开发近似估计算法。将该算法的结果与钢琴录音中的其他算法进行了比较。

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