最佳化梅爾倒頻譜係數之研究及其於音樂曲風辨識之應用

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Title:	最佳化梅爾倒頻譜係數之研究及其於音樂曲風辨識之應用
Authors:	周智勳 Chou, Chih-Hsun
Contributors:	資訊工程學系 Computer Science & Information Engineering
Keywords:	梅爾倒頻譜係數;基因演算法權重;曲風分類 MFCCs;genetic algorithms;music genre classification
Date:	2010
Issue Date:	2014-06-27 01:38:45 (UTC+8)
Abstract:	在音樂辨識系統中，梅爾倒頻譜係數被廣泛的運用在音訊及音樂資料庫的分類決策，而隨著梅爾倒頻譜係數的運用，不少梅爾倒頻譜係數的改良方法也隨之被提出，其中針對三角濾波器能量組進行權重調整以提升辨識效果的方法被證實是可行的。本篇論文嘗試以基因演算法尋找最佳辨識效果之權重，並應用在曲風辨識上。實驗過程針對比賽用之資料庫ISMIR，並得到明顯的改良效果。 Due to the wide applications of MFCCs in the audio signal processing, a lot of studies on the improvement of MFCCs were presented. Among them, the improvement of the weightings of the triangular filters is a worth study. In this study, genetic algorithms
Appears in Collections:	[Department of Computer Science and Information Engineering] Journal Articles

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