A phrase-level piecewise linear scaling algorithm for melody match in query-by-humming systems

  • Authors:

  • Wenxiao Cao;Danning Jiang;Jue Hou;Yong Qin;Thomas Fang Zheng;Yi Liu

  • Affiliations:

  • Center for Speech and Language Technologies, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China;IBM China Research Lab, Beijing, China;Center for Speech and Language Technologies, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China;IBM China Research Lab, Beijing, China;Center for Speech and Language Technologies, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China;Center for Speech and Language Technologies, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China

  • Venue:
  • ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
  • Year:
  • 2009

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Abstract

The Query-by-Humming (QBH) system allows users to retrieve songs by singing/humming. In this paper we propose a phrase-level piecewise linear scaling algorithm for melody match. Musical phrase boundaries are predicted for the query to split it to phrases. The boundaries of melody fragment corresponding to each phrase are allowed for adjusting in a limited scope. The algorithm employs Dynamic Programming and Recursive Alignment to search for the minimal piecewise matching cost upon Linear Scaling at phrase-level. Our experimental results on 5223 melody database show that the proposed algorithm outperforms traditional algorithms. The proposed algorithm gives significant improvements of 17.0%, 14.7% and 4.8% with respect to Linear Scaling, Dynamic Time Wrapping and Recursive Alignment in top-1 rate, respectively. The results show that the proposed algorithm is more efficient than the previous algorithms.