Factors Affecting Automatic Genre Classification: An Investigation Incorporating Non-Western Musical Forms
Factors Affecting Automatic Genre Classification: An Investigation Incorporating Non-Western Musical Forms
复制标题
影响自动流派分类的因素：一项纳入非西方音乐形式的调查
DOI：
--
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
R. Rahmat
中科院分区：
文献类型：
--
作者：
N. Norowi;S. Doraisamy;R. Rahmat
随着可用的数字音频数据数量的增加，研究自动流派分类的研究数量也在增加。执行自动体裁分类的基本技术一般包括特征提取和分类。在这项研究中，使用Marsyas来提取音频特征，并使用WEKA中提供的一套工具进行分类。本研究探讨了影响语类自动分类的因素。至于数据集，这方面的研究大多涉及西方流派，传统的马来音乐也被纳入这项研究。介绍了八种体裁：Dikir Barat，Etnik Sabah，Inang，Joget，Keroncong，Tumbuk Kalang，Wayang Kulit和Zapin。总共收集了来自各种音频光盘的417首曲目并用作数据集。结果表明，所提取的音乐特征、所采用的分类器、数据集的大小、摘录长度、摘录位置和测试集参数等各种因素都改善了分类结果。
The number of studies investigating automated genre classification is growing following the increasing amounts of digital audio data available. The underlying techniques to perform automated genre classification in general include feature extraction and classification. In this study, MARSYAS was used to extract audio features and the suite of tools available in WEKA was used for the classification. This study investigates the factors affecting automated genre classification. As for the dataset, most studies in this area work with western genres and traditional Malay music is incorporated in this study. Eight genres were introduced; Dikir Barat, Etnik Sabah, Inang, Joget, Keroncong, Tumbuk Kalang, Wayang Kulit, and Zapin. A total of 417 tracks from various Audio Compact Discs were collected and used as the dataset. Results show that various factors such as the musical features extracted, classifiers employed, the size of the dataset, excerpt length, excerpt location and test set parameters improve classification results.