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哼唱檢索的辨識方法改進及探討
Thesis

哼唱檢索的辨識方法改進及探討

李念容
Masters, 國立清華大學, 資訊工程學系
2006

Abstract

旋律辨識
Dynamic time warping (DTW) is a very effective method for query by singing/humming (QBSH), but it requires a lot of computation. On the other hand, linear scaling (LS) requires much less time on computation, but it is not as effective as DTW. As a result, in this thesis, our goal is to find new methods that can combine the advantages of DTW and LS for efficient and effective music retrieval in QBSH systems. Specifically, we have proposed two methods in this thesis, segmented linear scaling (SLS) and note-based linear scaling (NBLS). We have performed extensive experiments to demonstrate that the proposed methods can indeed combine the effectiveness of DTW and efficiency of LS to construct a more practical QBSH system. Conclusions and future work are also addressed in the thesis.

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