图 书 馆
比较旋律序列的概率模型Comparing Probabilistic Models for Melodic Sequences |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_spiliopoulou_melodic/ |
| 主讲教师: | Athina Spiliopoulou |
| 开课单位: | 爱丁堡大学 |
| 开课时间: | 2011-11-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM. |
| 关 键 词: | 模拟; 机器学习; 概率模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-03：lxf |
| 阅读次数: | 80 |