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dc.contributor.author Modipa, T
dc.contributor.author Davel, M
dc.contributor.author De Wet, Febe
dc.date.accessioned 2012-03-06T09:58:15Z
dc.date.available 2012-03-06T09:58:15Z
dc.date.issued 2010-10
dc.identifier.citation Modipa, T, Davel, M and De Wet, F. Acoustic modelling of Sepedi affricates for ASR. 2010 Annual Research Conference of the South African Institute for Computer Scientists and Information Technologists (SAICSIT 2010), Bela Bela, South Africa, 11-13 October 2010 en_US
dc.identifier.isbn 978-1-60558-950-3
dc.identifier.uri http://delivery.acm.org/10.1145/1900000/1899552/p394-modipa.pdf?ip=146.64.81.8&acc=ACTIVE%20SERVICE&CFID=88545526&CFTOKEN=51832324&__acm__=1331025181_6c0810155717926dddd97de90a1b4bf0
dc.identifier.uri http://hdl.handle.net/10204/5631
dc.description 2010 Annual Research Conference of the South African Institute for Computer Scientists and Information Technologists (SAICSIT 2010), Bela Bela, South Africa, 11-13 October 2010. This is an ABSTRACT ONLY en_US
dc.description.abstract Automatic speech recognition (ASR) systems are increasingly being developed for under-resourced languages, especially for use in multilingual spoken dialogue systems. We investigate different approaches to the acoustic modelling of Sepedi affricates for ASR. We determine that it is possible to model various of these complex consonants as a sequence of much simpler sounds. This approach reduces the Sepedi phoneme inventory from 45 to 32, resulting in simpler dictionary development and transcription processes, as well as more accurate acoustic modelling. en_US
dc.language.iso en en_US
dc.publisher ACM Digital Library en_US
dc.relation.ispartofseries Workflow;5161
dc.subject Artificial intelligence en_US
dc.subject Natural language processing en_US
dc.subject Speech recognition and synthesis en_US
dc.subject Sepedi en_US
dc.subject Acoustic models en_US
dc.subject Phonemes en_US
dc.subject Affricates en_US
dc.title Acoustic modelling of Sepedi affricates for ASR en_US
dc.type Presentation en_US


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