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An MELP Vocoder Based on UVS and MVF

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Machine Learning and Intelligent Communications (MLICOM 2016)

Abstract

Mixed excitation linear prediction (MELP) vocoder is generally used in low bit-rate vocoder, whose target now focuses on overall coding scheme, decrease of coding rate and improvement of robustness. Unvoiced/voiced/silence detective algorithm (UVS) possesses certain robustness and anti-noise property, while voiced excitation model based on maximum voicing frequency algorithm (MVF) is closer to the original speech characteristics. In this paper, the original excitation model of MELP vocoder is replaced and UVS is joined so that an improved 2.4 kbps coding rate vocoder is accomplished. Compared with MELP of federal standards, the improved vocoder owns better synthetic speech quality and robustness.

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Correspondence to Xiaoqun Zhao .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lu, T., Zhao, X. (2017). An MELP Vocoder Based on UVS and MVF. In: Xin-lin, H. (eds) Machine Learning and Intelligent Communications. MLICOM 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-319-52730-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-52730-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52729-1

  • Online ISBN: 978-3-319-52730-7

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