Abstract
We present in this paper a novel system for query by humming, our method differs from other ones in the followings: Firstly, we use recurrent neural network as the index of music database. Secondly, we present correlation degree to evaluate the music matching precision. We now hold a database of 201 pieces of music with various genres. The result of our experiment reports that the successful rate is 63% with top one matching and 87% with top three matching. Future work will be on melody extraction technique from popular formats of music and on-line music retrieval.
Cite
CITATION STYLE
Yahzong, F., Yueting, Z., & Yunhe, P. (2001). Query similar music by correlation degree. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2195, pp. 885–890). Springer Verlag. https://doi.org/10.1007/3-540-45453-5_116
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