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International Conference in Communications, Signal Processing, and Systems

CSPS 2018: Communications, Signal Processing, and Systems pp 233–243Cite as

An Improved Speech Synthesis Algorithm with Post filter Parameters Based on Deep Neural Network

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 517))

Abstract

Statistical parameters speech synthesis typically relies on context-dependent Hidden Markov Model (HMM) that is based on decision tree clustering. However, the shortcomings of clustering decision tree, restricted to a feature rigid subdivision model space, results in smooth speech parameters generated from HMM. In this paper, Deep Neural Network (DNN) is put forward to replace clustering decision tree, and we propose a post filter-parameter-based speech synthesis improvement algorithm. This method enhances the formant region of synthesized speech spectrum by selecting the most optimized filter parameter according to the flatness of spectrum. The experimental results show that DNN effectively can modify the deficiency of two smooth parameters. Furthermore, the improved post filter algorithm increases the naturalness of synthesized speech.

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Acknowledgements

This paper is supported by the URTP project of School of SME, the demonstration course project of Xidian University, and the Ministry of Education cooperation collaborative education project.

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Authors and Affiliations

  1. School of Microelectronics, Xidian University, Xi’an, China

    Shunjie Dong & Hong Zhang

  2. School of Computer Science and Technology, Xidian University, Xi’an, China

    Chunyang Li

Authors
  1. Shunjie Dong
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  2. Chunyang Li
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  3. Hong Zhang
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Corresponding author

Correspondence to Hong Zhang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Dong, S., Li, C., Zhang, H. (2020). An Improved Speech Synthesis Algorithm with Post filter Parameters Based on Deep Neural Network. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_30

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  • DOI: https://doi.org/10.1007/978-981-13-6508-9_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6507-2

  • Online ISBN: 978-981-13-6508-9

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