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Free Tools and Resources for HMM-Based Brazilian Portuguese Speech Synthesis

  • Conference paper
Advances in Artificial Intelligence – IBERAMIA 2018 (IBERAMIA 2018)

Abstract

Text-to-speech (TTS) is currently a mature technology used in many areas such as education and accessibility. Some modules of a TTS system depend on the language and, while there are many public materials for some languages (e.g., English and Japanese), the resources for Brazilian Portuguese (BP) are still limited. This work describes the development of a complete hidden Markov model (HMM) based TTS system for BP which can be applied to the desktop environment. It also releases a set of natural language processing tools for BP, which expands the already publicly available resources, supporting the development of new researches for academic or industrial purposes. Subjective and objective performance tests are presented, comparing the proposed TTS system with other softwares currently available for BP.

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Notes

  1. 1.

    The syllable is a unit relatively easy to identify and segmental if the splitting rules stipulated by the language orthography are followed. However, as a phonological unit, there is no consensus about its basic structure, as discussed in [9]. For most authors, a syllable is defined so that its nucleus, canonically a vowel, constitutes a peak in the curve of audibility that is preceded (onset) and/or followed (coda) by a sequence of segments (none or more consonants), with progressively decreasing sonority values. The nucleus and coda are sometimes lumped together to form what is called the rhyme. By applying these principles, the syllable is a speech unit of rhythmic organization, although other authors disagree, stating that the syllable should not be seen in parts but as a whole.

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Correspondence to Ericson Costa or Nelson Neto .

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Costa, E., Neto, N. (2018). Free Tools and Resources for HMM-Based Brazilian Portuguese Speech Synthesis. In: Simari, G.R., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J.A. (eds) Advances in Artificial Intelligence – IBERAMIA 2018. IBERAMIA 2018. Lecture Notes in Computer Science(), vol 11238. Springer, Cham. https://doi.org/10.1007/978-3-030-03928-8_30

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  • DOI: https://doi.org/10.1007/978-3-030-03928-8_30

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03927-1

  • Online ISBN: 978-3-030-03928-8

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