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Query Similar Music by Correlation Degree

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Book cover Advances in Multimedia Information Processing — PCM 2001 (PCM 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2195))

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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.

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Author information

Authors and Affiliations

  1. Institute of Artificial Intelligence, Zhejiang University, Hangzhou, 310027, P. R. China

    Zhuang Yueting & Pan Yunhe

Authors
  1. Feng Yahzong
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  2. Zhuang Yueting
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  3. Pan Yunhe
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Editor information

Editors and Affiliations

  1. Microsoft Research China, 5/F Beijing Sigma Center 49 Zhichung Road, Haidian District, Beijing, 100080, China

    Heung-Yeung Shum

  2. Institute of Information Science, Academia Sinica, Taiwan

    Mark Liao

  3. Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA

    Shih-Fu Chang

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© 2001 Springer-Verlag Berlin Heidelberg

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Yahzong, F., Yueting, Z., Yunhe, P. (2001). Query Similar Music by Correlation Degree. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_116

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  • DOI: https://doi.org/10.1007/3-540-45453-5_116

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42680-6

  • Online ISBN: 978-3-540-45453-3

  • eBook Packages: Springer Book Archive

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