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Collecting and evaluating speech recognition corpora for 11 South African languages

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dc.contributor.author Badenhorst, J
dc.contributor.author Van Heerden, C
dc.contributor.author Davel, M
dc.contributor.author Barnard, E
dc.date.accessioned 2012-04-16T15:44:28Z
dc.date.available 2012-04-16T15:44:28Z
dc.date.issued 2011-08
dc.identifier.citation Badenhorst, J, Van Heerden, C, Davel, M and Barnard, E. 2011. Collecting and evaluating speech recognition corpora for 11 South African languages. Language Resources and Evaluation, vol. 45(3), pp 289-309 en_US
dc.identifier.issn 1574-020X
dc.identifier.issn 1574-0218
dc.identifier.uri http://www.springerlink.com/content/m772051343jg875k/fulltext.pdf
dc.identifier.uri http://hdl.handle.net/10204/5770
dc.description Copyright: 2011 Springer-Verlag. This is the pre-print version of the work. The definitive version is published in Language Resources and Evaluation, vol. 45(3), pp 289-309 en_US
dc.description.abstract The authors describe the Lwazi corpus for automatic speech recognition (ASR), a new telephone speech corpus which contains data from the eleven official languages of South Africa. Because of practical constraints, the amount of speech per language is relatively small compared to major corpora in world languages, and they report on their investigation of the stability of the ASR models derived from the corpus. They also report on phoneme distance measures across languages, and describe initial phone recognisers that were developed using this data. They find that a surprisingly small number of speakers (fewer than 50) and around 10 to 20 hours of speech per language are sufficient for the purposes of acceptable phone-based recognition. en_US
dc.language.iso en en_US
dc.publisher Springer Science+Business Media B.V. en_US
dc.relation.ispartofseries Workflow;8149
dc.subject South Afrcan languages en_US
dc.subject Lwazi corpus en_US
dc.subject Automatic speech recognition (ASR) en_US
dc.subject Speech recognition en_US
dc.subject Speech recognition evaluation en_US
dc.title Collecting and evaluating speech recognition corpora for 11 South African languages en_US
dc.type Article en_US
dc.identifier.apacitation Badenhorst, J., Van Heerden, C., Davel, M., & Barnard, E. (2011). Collecting and evaluating speech recognition corpora for 11 South African languages. http://hdl.handle.net/10204/5770 en_ZA
dc.identifier.chicagocitation Badenhorst, J, C Van Heerden, M Davel, and E Barnard "Collecting and evaluating speech recognition corpora for 11 South African languages." (2011) http://hdl.handle.net/10204/5770 en_ZA
dc.identifier.vancouvercitation Badenhorst J, Van Heerden C, Davel M, Barnard E. Collecting and evaluating speech recognition corpora for 11 South African languages. 2011; http://hdl.handle.net/10204/5770. en_ZA
dc.identifier.ris TY - Article AU - Badenhorst, J AU - Van Heerden, C AU - Davel, M AU - Barnard, E AB - The authors describe the Lwazi corpus for automatic speech recognition (ASR), a new telephone speech corpus which contains data from the eleven official languages of South Africa. Because of practical constraints, the amount of speech per language is relatively small compared to major corpora in world languages, and they report on their investigation of the stability of the ASR models derived from the corpus. They also report on phoneme distance measures across languages, and describe initial phone recognisers that were developed using this data. They find that a surprisingly small number of speakers (fewer than 50) and around 10 to 20 hours of speech per language are sufficient for the purposes of acceptable phone-based recognition. DA - 2011-08 DB - ResearchSpace DP - CSIR KW - South Afrcan languages KW - Lwazi corpus KW - Automatic speech recognition (ASR) KW - Speech recognition KW - Speech recognition evaluation LK - https://researchspace.csir.co.za PY - 2011 SM - 1574-020X SM - 1574-0218 T1 - Collecting and evaluating speech recognition corpora for 11 South African languages TI - Collecting and evaluating speech recognition corpora for 11 South African languages UR - http://hdl.handle.net/10204/5770 ER - en_ZA


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