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Browsing by Author "Badenhorst, J"

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  • Rashamuse, KJ; Visser, Daniel F; Hennessy, F; Kemp, J; Van der Merwe, MP; Badenhorst, J; Ronneburg, T; Francis-Pope, R; Brady, D (Springer Verlag, 2013-02)
    Ruminant digestive tract microbes hydrolyse plant biomass, and the application of metagenomic techniques can provide good coverage of their glycosyl hydrolase enzymes. A metagenomic library of circa 70,000 fosmids was ...
  • Badenhorst, J; Van Heerden, C; Davel, M; Barnard, E (Springer Science+Business Media B.V., 2011-08)
    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 ...
  • De Wet, Febe; Badenhorst, J; Modipa, T (Elsevier, 2016-05)
    The official languages of South Africa can still be classified as under-resourced with respect to the speech resources that are required for technology development. Harvesting speech data from existing sources is one means ...
  • Badenhorst, J; Davel, MH; Barnard, E (PRASA, 2012-11)
    We improve on a piece-wise linear model of the trajectories of Mel Frequency Cepstral Coefficients, which are commonly used as features in Automatic Speech Recognition. For this purpose, we have created a very clean ...
  • Kesavan Pillai, Sreejarani; Sinha Ray, S; Scriba, M; Bandyopadhyay, J; Roux-van der Merwe, MP; Badenhorst, J (Elsevier, 2013-10)
    Silver (Ag)/montmorillonite (Mt) heterostructures were effectively synthesized utilising microwave (MW) irradiation technique in the absence of any reducing agent. Compared to conventional thermal reduction processes, this ...
  • Barnard, E; Davel, MH; Van Heerden, C; De Wet, Febe; Badenhorst, J (2014-05)
    The NCHLT speech corpus contains wide-band speech from approximately 200 speakers per language, in each of the eleven of cial languages of South Africa. We describe the design and development processes that were undertaken ...
  • Badenhorst, J; De Waal, A; De Wet, Febe (2012-05)
    The collection of speech data suitable for speech technology development is a challenge for under-resourced languages. Factors such as cost, availability of mother-tongue speakers and vast geographic distances call for ...
  • De Vries, NJ; Davel, MH; Badenhorst, J; Basson, WD; De Wet, Febe; Barnard, E; De Waal, A (Elsevier, 2014-01)
    Acoustic data collection for automatic speech recognition (ASR) purposes is a particularly challenging task when working with under resourced languages, many of which are found in the developing world. We provide a brief ...
  • Badenhorst, J; Davel, MH (IEEE, 2015-11)
    We experiment with a new method to create synthetic models of rare and unseen triphones in order to supplement limited automatic speech recognition (ASR) training data. A trajectory model is used to characterise seen ...
  • Badenhorst, J; Davel, MH; Barnard, E (PRASA, 2011-11)
    The authors propose a piecewise-linear model for the temporal trajectories of Mel Frequency Cepstral Coefficients during phone transitions. As with conventional Hidden Markov Models, the parameters of the model can be ...
  • De Vries, NJ; Badenhorst, J; Davel, MH; Barnard, E; De Waal, A (Conference paper, 2011-08)
    Building transcribed speech corpora for under-resourced languages plays a pivotal role in developing speech technologies for such languages. The authors have developed an open-source tool for devices running the Android ...