Author:De Wet, Febe; Dlamini, Nkosikhona; Van der Walt, Willem J; Govender, AvashnaDate:Dec 2017Creating synthetic voices that are both natural and intelligible is a daunting challenge for well-resourced languages. The challenge is much bigger for languages in which the speech and text resources required for voice development are not ...Read more
Author:Davel, MH; Van Heerden, C; Kleynhans, N; Barnard, EDate:Aug 2011Spoken recordings that have been transcribed for human reading (e.g. as captions for audiovisual material, or to provide alternative modes of access to recordings) are widely available in many languages. Such recordings and transcriptions ...Read more
Author:Van Heerden, C; Kleynhans, N; Barnard, E; Davel, MDate:May 2010We describe several experiments that were conducted to assess the viability of data pooling as a means to improve speech-recognition performance for under-resourced languages. Two groups of closely related languages from the Southern Bantu ...Read more
Author:Badenhorst, J; De Waal, A; De Wet, FebeDate:May 2012The 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 techniques to optimise ...Read more
Author:Kamper, H; De Wet, Febe; Hain, T; Niesler, TDate:May 2012We present a description of the development and evaluation of a first South African broadcast news transcription system. We describe a number of speech resources which have been collected in the resource-scarce South African environment for ...Read more
Author:Molapo, B; Barnard, E; De Wet, FebeDate:May 2014In this paper, we present an end-to-end solution to the development of an automatic speech recognition (ASR) system in typical under-resourced languages, where the target language is likely to be influenced by one more embedded foreign ...Read more
Author:Sefara, Tshephisho J; Modupe, AbiodunDate:Nov 2019The impressive improvement in performance obtained using neural networks for automatic speech recognition (ASR) have motivated the application of neural networks to other speech technologies such as speaker, emotion, language, and gender ...Read more