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Feature Space VTS with Phase Term Modeling

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Speech and Computer (SPECOM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9811))

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Abstract

A new variant of Vector Taylor Series based features compensation algorithm is proposed. The phase-sensitive speech distortion model is used and the phase term is modeled as a multivariate gaussian with unknown mean vector and covariance matrix. These parameters are estimated based on Maximum Likelihood principle and EM-algorithm is used for this. EM formulas of parameter update are derived as well MMSE estimate of the clean speech features. The experiments on Aurora2 database show that taking phase term into account and data-driven estimation of its parameters result in relative WER reduction of about 20 % compared to phase-insensitive VTS version. The proposed method is also compared to the VTS with constant phase vector and this approximation is shown to be very efficient.

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Notes

  1. 1.

    In what follows we deal with only mel-cepstral domain since log-spectral domain is similar but more simple to explore.

  2. 2.

    The equation (13) holds when noise and phase vectors are considered as independent. Otherwise the additional cross-correlation term appears.

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Acknowledgments

This work was financially supported by the Ministry of Education and Science of the Russian Federation, Contract 14.575.21.0033 (ID RFMEFI57514X0033).

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Authors and Affiliations

  1. ITMO University, Saint Petersburg, Russia

    Maxim Korenevsky & Aleksei Romanenko

  2. STC-Innovations Ltd., Saint Petersburg, Russia

    Maxim Korenevsky

Authors
  1. Maxim Korenevsky
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  2. Aleksei Romanenko
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Corresponding author

Correspondence to Maxim Korenevsky .

Editor information

Editors and Affiliations

  1. SPIIRAS , Saint-Petersburg, Russia

    Andrey Ronzhin

  2. Moscow State Linguistic University , Moscow, Russia

    Rodmonga Potapova

  3. Budapest University of Technology and Economics, Budapest, Hungary

    Géza Németh

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Korenevsky, M., Romanenko, A. (2016). Feature Space VTS with Phase Term Modeling. In: Ronzhin, A., Potapova, R., Németh, G. (eds) Speech and Computer. SPECOM 2016. Lecture Notes in Computer Science(), vol 9811. Springer, Cham. https://doi.org/10.1007/978-3-319-43958-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-43958-7_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43957-0

  • Online ISBN: 978-3-319-43958-7

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