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Proceedings of SAI Intelligent Systems Conference

IntelliSys 2019: Intelligent Systems and Applications pp 61–66Cite as

Emotional Speech Datasets for English Speech Synthesis Purpose: A Review

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

Abstract

In this paper, we review the datasets of emotional speech publicly available and their usability for state of the art speech synthesis. This is conditioned by several characteristics of these datasets: the quality of the recordings, the quantity of the data and the emotional content captured contained in the data. We then present a dataset that was recorded based on the observation of the needs in this area. It contains data for male and female actors in English and a male actor in French. The database covers five emotion classes so it could be suitable to build synthesis and voice transformation systems with the potential to control the emotional dimension.

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Notes

  1. 1.

    https://github.com/numediart/EmoV-DB.

  2. 2.

    https://github.com/numediart/EmoV-DB.

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Acknowledgments

Noé Tits is funded through a PhD grant from the Fonds pour la Formation à la Recherche dans l’Industrie et l’Agriculture (FRIA), Belgium.

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Authors and Affiliations

  1. Numediart Institute, University of Mons, 7000, Mons, Belgium

    Noé Tits, Kevin El Haddad & Thierry Dutoit

Authors
  1. Noé Tits
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  2. Kevin El Haddad
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  3. Thierry Dutoit
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Corresponding author

Correspondence to Noé Tits .

Editor information

Editors and Affiliations

  1. School of Computing, Computer Science Research Institute, Ulster University, Newtownabbey, UK

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Tits, N., El Haddad, K., Dutoit, T. (2020). Emotional Speech Datasets for English Speech Synthesis Purpose: A Review. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_6

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