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Rhonda: The architecture of a multilingual speech-to-speech translation pipeline

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dc.contributor.author Louw, Johannes A
dc.contributor.author Moodley, Avashlin
dc.date.accessioned 2020-03-24T09:03:37Z
dc.date.available 2020-03-24T09:03:37Z
dc.date.issued 2018-12
dc.identifier.citation Louw, J.A. and Moodley, A. 2018. Rhonda: The architecture of a multilingual speech-to-speech translation pipeline. 2018 International Conference on Intelligent & Innovative Computing Applications (ICONIC), Holiday Inn Mon Tresor, Mauritius, 6-7 December 2018, pp 194-200. en_US
dc.identifier.isbn 978-1-5386-6477-3
dc.identifier.uri https://ieeexplore.ieee.org/document/8601204/
dc.identifier.uri DOI: 10.1109/ICONIC.2018.8601204
dc.identifier.uri tp://mauricon.org/
dc.identifier.uri http://mauricon.org/wp-content/uploads/2018/12/Mauricon-2018-Conference-Proceedings-44423-041218.pdf
dc.identifier.uri http://hdl.handle.net/10204/11378
dc.description Copyright: 2018 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, kindly consult the publisher's website en_US
dc.description.abstract Speech-to-speech translation can be described as converting a speech signal from a source language into a speech signal of the same meaning or intent into a target language. This process is achieved by the coordinated cooperation of individual Human Language Technology components, where the most important components to a speech translation system are automatic speech recognition, machine translation and text-to-speech. In this paper we present and discuss the design and architectural building blocks of the Rhonda speech-to-speech translation system, as well as their interactions with each other to facilitate speech-to-speech translation in a reliable, scalable and possibly distributed manner. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;21831
dc.subject Automatic speech en_US
dc.subject Machine translation en_US
dc.subject Multilingual en_US
dc.subject Recognition en_US
dc.subject Speech-to-speech translation en_US
dc.subject Text-to-speech en_US
dc.title Rhonda: The architecture of a multilingual speech-to-speech translation pipeline en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Louw, J. A., & Moodley, A. (2018). Rhonda: The architecture of a multilingual speech-to-speech translation pipeline. IEEE. http://hdl.handle.net/10204/11378 en_ZA
dc.identifier.chicagocitation Louw, Johannes A, and Avashlin Moodley. "Rhonda: The architecture of a multilingual speech-to-speech translation pipeline." (2018): http://hdl.handle.net/10204/11378 en_ZA
dc.identifier.vancouvercitation Louw JA, Moodley A, Rhonda: The architecture of a multilingual speech-to-speech translation pipeline; IEEE; 2018. http://hdl.handle.net/10204/11378 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Louw, Johannes A AU - Moodley, Avashlin AB - Speech-to-speech translation can be described as converting a speech signal from a source language into a speech signal of the same meaning or intent into a target language. This process is achieved by the coordinated cooperation of individual Human Language Technology components, where the most important components to a speech translation system are automatic speech recognition, machine translation and text-to-speech. In this paper we present and discuss the design and architectural building blocks of the Rhonda speech-to-speech translation system, as well as their interactions with each other to facilitate speech-to-speech translation in a reliable, scalable and possibly distributed manner. DA - 2018-12 DB - ResearchSpace DP - CSIR KW - Automatic speech KW - Machine translation KW - Multilingual KW - Recognition KW - Speech-to-speech translation KW - Text-to-speech LK - https://researchspace.csir.co.za PY - 2018 SM - 978-1-5386-6477-3 T1 - Rhonda: The architecture of a multilingual speech-to-speech translation pipeline TI - Rhonda: The architecture of a multilingual speech-to-speech translation pipeline UR - http://hdl.handle.net/10204/11378 ER - en_ZA


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