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Can Style be Learned? A Machine Learning Approach Towards ‘Performing’ as Famous Pianists[风格可以学到什么？一种针对著名钢琴家Can Style be Learned? A Machine Learning Approach Towards ‘Performing’ as Famous Pianists[风格可以学到什么？一种针对著名钢琴家 |
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| 课程网址: | http://videolectures.net/mbc07_dorard_csl/ |
| 主讲教师: | Louis Dorard |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2008-02-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper a novel method for performing music in the style of famous pianists is presented. We use Kernel Canonical Correlation Analysis (KCCA), a method which looks for a common semantic representation between two views, to learn the correlation between a representation of a musical score and a representation of an artist’s performance of that score. We use the performance representation based on the variations of beat level global loudness and tempo through time, as suggested by [3]. Therefore, the crux of the matter is the representation of the musical scores and by implication a similarity measure between relevant features that capture our prior knowledge of music. We therefore proceed to propose a novel kernel for musical scores, which is a Gaussian kernel adaptation to the distances between rhythm patterns, melodic contours and chords progressions. |
| 关 键 词: | 著名钢琴家; 演奏音乐; 相关分析; 高斯内核; 节奏模式 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-05-24：吴雨秋(课程编辑志愿者) |
| 阅读次数: | 47 |