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Unified Language-Independent DNN-Based G2P Converter

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955898" target="_blank" >RIV/49777513:23520/19:43955898 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2335.pdf" target="_blank" >https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2335.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21437/Interspeech.2019-2335" target="_blank" >10.21437/Interspeech.2019-2335</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Unified Language-Independent DNN-Based G2P Converter

  • Original language description

    We introduce a unified Grapheme-to-phoneme conversion framework based on the composition of deep neural networks. In contrary to the usual approaches building the G2P frameworks from the dictionary, we use whole phrases, which allows us to capture various language properties, e.g. cross-word assimilation, without the need for any special care or topology adjustments. The evaluation is carried out on three different languages -- English, Czech and Russian. Each requires dealing with specific properties, stressing the proposed framework in various ways. The very first results show promising performance of the proposed framework, dealing with all the phenomena specific to the tested languages. Thus, we consider the framework to be language-independent for a wide range of languages.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/GA19-19324S" target="_blank" >GA19-19324S: Fully Trainable Deep Neural Network Based Czech Text-to-Speech Synthesis</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 20th Annual Conference of the International Speech Communication Association (Interspeech 2019)

  • ISBN

    978-1-5108-9683-3

  • ISSN

    2308-457X

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    2085-2089

  • Publisher name

    Curran Associates, Inc.

  • Place of publication

    Red Hook, NY

  • Event location

    Graz, Austria

  • Event date

    Sep 15, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article