Effectiveness of N-gram fast match for query-by-humming systems

  • Authors:

  • Jue Hou;Dan-ning Jiang;Wen-xiao Cao;Yong Qin;Thomas Fang Zheng;Yi Liu

  • Affiliations:

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

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

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Abstract

To achieve a good balance between matching accuracy and computation efficiency is a key challenge for Query-by-Humming (QBH) system. In this paper, we propose an approach of n-gram based fast match. Our n-gram method uses a robust statistical note transcription as well as error compensation method based on the analysis of frequent transcription errors. The effectiveness of our approach has been evaluated on a relatively large melody database with 5223 melodies. The experimental results show that when the searching space was reduced to only 10% of the whole size, 90% of the target melodies were preserved in the candidates, and 88% of the match accuracy of system was kept. Meanwhile, no obvious additional computation was applied.