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Unified Algorithm for Melodic Music Similarity and Retrieval in Query by Humming

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Intelligent Computing and Information and Communication

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 673))

Abstract

Query by humming (QBH) is an active research area since a decade with limited commercial success. Challenges include partial imperfect queries from users, query representation and matching, fast, and accurate generation of results. Our work focus is on query presentation and matching algorithms to reduce the effective computational time and improve accuracy. We have proposed a unified algorithm for measuring melodic music similarity in QBH. It involves two different approaches for similarity measurement. They are novel mode normalized frequency algorithm using edit distance and n-gram precomputed inverted index method. This proposed algorithm is based on the study of melody representation in the form of note string and user query variations. Queries from four non-singers with no formal training of singing are used for initial testing. The preliminary results with 60 queries for 50 songs database are encouraging for the further research.

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Acknowledgements

The authors gratefully acknowledge the support by MKSSS’s Cummins College of Engineering for providing experimental setup and the efforts by our UG students Aditi Pawle, Snehal Jain, Sonal Gawande, and Sonal Avhad for the active help in preparing query samples and experiments. Volunteer singer’s contribution for generating queries is highly appreciable. We would like to thank Dr. Sahasrabuddhe H. V. for his valuable suggestions and inputs related to musical knowledge and experiments.

Author information

Authors and Affiliations

  1. Cummins College of Engineering, Pune, India

    Velankar Makarand

  2. Iknowlation Research Labs Pvt. Ltd, Pune, India

    Kulkarni Parag

Authors
  1. Velankar Makarand
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  2. Kulkarni Parag
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Corresponding author

Correspondence to Velankar Makarand .

Editor information

Editors and Affiliations

  1. Department of Computer Software, University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Subhash Bhalla

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of Information Technology, MIT College of Engineering, Pune, Maharashtra, India

    Anjali A. Chandavale

  4. Department of Information Technology, MIT College of Engineering, Pune, Maharashtra, India

    Anil S. Hiwale

  5. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

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Makarand, V., Parag, K. (2018). Unified Algorithm for Melodic Music Similarity and Retrieval in Query by Humming. In: Bhalla, S., Bhateja, V., Chandavale, A., Hiwale, A., Satapathy, S. (eds) Intelligent Computing and Information and Communication. Advances in Intelligent Systems and Computing, vol 673. Springer, Singapore. https://doi.org/10.1007/978-981-10-7245-1_37

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  • DOI: https://doi.org/10.1007/978-981-10-7245-1_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7244-4

  • Online ISBN: 978-981-10-7245-1

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