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dc.contributor.authorBasson, Willem D.
dc.contributor.authorDavel, Marelie H.
dc.date.accessioned2014-11-03T14:23:04Z
dc.date.available2014-11-03T14:23:04Z
dc.date.issued2012
dc.identifier.citationBasson, W.D. & Davel, M.H. 2012. Comparing grapheme-based and phoneme-based speech recognition for Afrikaans. Proceedings of the Twenty-Third Annual Symposium of the Pattern Recognition Association of South Africa. Pretoria. p. 144-148. [http://www.prasa.org/]en_US
dc.identifier.isbn978-0-620-54601-0
dc.identifier.urihttp://hdl.handle.net/10394/12122
dc.identifier.urihttps://www.researchgate.net/publication/235425731_Comparing_grapheme-based_and_phoneme-based_speech_recognition_for_Afrikaans?channel=doi&linkId=0a85e537dcdbf2cb85000000&showFulltext=true
dc.description.abstractThis paper compares the recognition accuracy of a phoneme-based automatic speech recognition system with that of a grapheme-based system, using Afrikaans as case study. The first system is developed using a conventional pronunciation dictionary, while the latter system uses the letters of each word directly as the acoustic units to be modelled. We ensure that the pronunciation dictionary we use is highly accurate and then investigate the extent to which ASR performance degrades when the dictionary is removed. We analyse this effect at different data set sizes and classify the causes of performance degradation. With grapheme-based ASR outperforming phoneme-based ASR in certain word categories, we find that relative error rates are highly dependent on word category, which points towards strategies for compensating for grapheme-based inaccuraciesen_US
dc.language.isoenen_US
dc.publisherPRASAen_US
dc.subjectSpeech recognition
dc.subjectP2G transliteration
dc.subjectPhoneme-to-grapheme rules
dc.subjectGrapheme-based ASR
dc.titleComparing grapheme-based and phoneme-based speech recognition for Afrikaansen_US
dc.typeArticleen_US
dc.contributor.researchID10066950 - Basson, Willem Diederick
dc.contributor.researchID23607955 - Davel, Marelie Hattingh


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