dc.contributor.author |
Louw, Johannes A
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dc.contributor.author |
Moodley, Avashlin
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dc.date.accessioned |
2020-03-24T09:03:37Z |
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dc.date.available |
2020-03-24T09:03:37Z |
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dc.date.issued |
2018-12 |
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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 |
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dc.identifier.uri |
https://ieeexplore.ieee.org/document/8601204/
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dc.identifier.uri |
DOI: 10.1109/ICONIC.2018.8601204
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dc.identifier.uri |
tp://mauricon.org/
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dc.identifier.uri |
http://mauricon.org/wp-content/uploads/2018/12/Mauricon-2018-Conference-Proceedings-44423-041218.pdf
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dc.identifier.uri |
http://hdl.handle.net/10204/11378
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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 |
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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 -
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en_ZA |