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Speech Data Enhancement Based on Hybrid Neural Network

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Advances in Multimedia Information Processing – PCM 2018 (PCM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11166))

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Abstract

With the rapid development of artificial intelligence, the recognition of speech, text, physiological signals and facial expressions has drawn more and more attention from scholars at home and abroad. Therefore, we cannot just study the problems of one area, but more we look for the similarities across fields. In this paper, the method of image enhancement is adapted according to the speech characteristics, and several feasible methods of speech data enhancement are proposed to avoid the problems of data collection and corpus limitation in speech emotion recognition. Based on the Hybrid neural network (Convolution Neural Network, CNN and Recurrent neural network, RNN) model, the feasibility and performance of the method are verified and showed through several sets of comparative experiments in different methods while a high recognition accuracy is obtained.

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Acknowledgment

The work is supported by the State Key Program of National Natural Science of China (61432004, 71571058, 61461045). This work was partially supported by the China Postdoctoral Science Foundation funded project (2017T100447). This research has been partially supported by National Natural Science Foundation of China under Grant No. 61472117. This work is also supported by the foundational application research of Qinghai Province Science and Technology Fund (No. 2016-ZJ-743).

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Authors and Affiliations

  1. School of Computer and Information, HeFei University of Technology, Hefei, Anhui, China

    Xinyue Cao, Xiao Sun & Fuji Ren

  2. School of Computer and Information, Tokushima University, Tokushima, Japan

    Fuji Ren

Authors
  1. Xinyue Cao
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  2. Xiao Sun
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  3. Fuji Ren
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Corresponding author

Correspondence to Xiao Sun .

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Editors and Affiliations

  1. Hefei University of Technology, Hefei, China

    Richang Hong

  2. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Huang Cheng

  3. University of Tokyo, Tokyo, Japan

    Toshihiko Yamasaki

  4. Hefei University of Technology, Hefei, China

    Meng Wang

  5. City University of Hong Kong, Hong Kong, Hong Kong

    Chong-Wah Ngo

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Cao, X., Sun, X., Ren, F. (2018). Speech Data Enhancement Based on Hybrid Neural Network. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11166. Springer, Cham. https://doi.org/10.1007/978-3-030-00764-5_33

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  • DOI: https://doi.org/10.1007/978-3-030-00764-5_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00763-8

  • Online ISBN: 978-3-030-00764-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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