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Detection of Singing Mistakes from Singing Voice

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Advances in Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 82))

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Abstract

We investigate a method of detecting the wrong lyrics from the singing voice. In the proposed method, we compare the input singing voice and the reference singing voice using dynamic time warping, and then observe the frame-by-frame distance to find the error location. However, the absolute value of the distance is affected by the singer individuality of the reference and input singing voice. Thus, we attempted to adapt the singer individuality into the reference singer’s one by a linear transformation. The results of the experiment showed that we could detect the wrong lyrics with high accuracy when the different part of the lyrics was long. In addition, we investigated the effect of iterative linear transformation, and we could not find any benefit from the second or third linear transformations.

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Author information

Authors and Affiliations

  1. Graduate School of Engineering, Tohoku University, Sendai, Japan

    Isao Miyagawa, Yuya Chiba, Takashi Nose & Akinori Ito

Authors
  1. Isao Miyagawa
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  2. Yuya Chiba
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  3. Takashi Nose
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  4. Akinori Ito
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Corresponding author

Correspondence to Akinori Ito .

Editor information

Editors and Affiliations

  1. Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Swinburne University of Technology, Hawthorn, Victoria, Australia

    Pei-Wei Tsai

  3. Universiti Teknologi Petronas, Teronoh, Malaysia

    Junzo Watada

  4. University of Canberra, Bruce, Aust Capital Terr, Australia

    Lakhmi C. Jain

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© 2018 Springer International Publishing AG

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Miyagawa, I., Chiba, Y., Nose, T., Ito, A. (2018). Detection of Singing Mistakes from Singing Voice. In: Pan, JS., Tsai, PW., Watada, J., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. IIH-MSP 2017. Smart Innovation, Systems and Technologies, vol 82. Springer, Cham. https://doi.org/10.1007/978-3-319-63859-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-63859-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63858-4

  • Online ISBN: 978-3-319-63859-1

  • eBook Packages: EngineeringEngineering (R0)

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