| Comparing different approaches for automatic pronunciation error detection H Strik, K Truong, F de Wet, C Cucchiarini Speech Communication 51 (10), 845-852, 2009 | 156 | 2009 |
| A smartphone-based ASR data collection tool for under-resourced languages NJ De Vries, MH Davel, J Badenhorst, WD Basson, F De Wet, E Barnard, ... Speech Communication 56, 119-131, 2014 | 106 | 2014 |
| The NCHLT speech corpus of the South African languages E Barnard, MH Davel, C van Heerden, F de Wet, J Badenhorst Proccedings of the 4th Workshop on Spoken Language Technologies for Under …, 2014 | 62 | 2014 |
| Comparing classifiers for pronunciation error detection H Strik, KP Truong, F Wet, C Cucchiarini Eighth Annual Conference of the International Speech Communication Association, 2007 | 48 | 2007 |
| Implications of Sepedi/English code switching for ASR systems TI Modipa, F De Wet, MH Davel Pattern recognition association of South Africa (PRASA), 2013 | 46 | 2013 |
| Automatic assessment of oral language proficiency and listening comprehension F De Wet, C Van der Walt, TR Niesler Speech Communication 51 (10), 864-874, 2009 | 44 | 2009 |
| Assessment of Dutch pronunciation by means of automatic speech recognition technology C Cucchiarini, F Wet, H Strik, LWJ Boves Sydney:[sn], 1998 | 34 | 1998 |
| Evaluation of formant-like features on an automatic vowel classification task F De Wet, K Weber, L Boves, B Cranen, S Bengio, H Bourlard The Journal of the Acoustical Society of America 116 (3), 1781-1792, 2004 | 31 | 2004 |
| Missing feature theory in ASR: make sure you miss the right type of features JM de Veth, F Wet, B Cranen, LWJ Boves Tampere, Finland:[sn], 1999 | 28 | 1999 |
| Automatic detection of frequent pronunciation errors made by L2-learners KP Truong, A Neri, F Wet, C Cucchiarini, H Strik Ninth European Conference on Speech Communication and Technology, 2005 | 27 | 2005 |
| Verifying pronunciation dictionaries using conflict analysis. MH Davel, F de Wet INTERSPEECH, 1898-1901, 2010 | 24 | 2010 |
| The origin of Afrikaans pronunciation: a comparison to west Germanic languages and Dutch dialects W Heeringa, F De Wet Proc. of the Conf. of the Pattern Recognition Association of South Africa …, 2008 | 18 | 2008 |
| Acoustic features and a distance measure that reduce the impact of training–test mismatch in ASR J De Veth, F de Wet, B Cranen, L Boves Speech Communication 34 (1-2), 57-74, 2001 | 18 | 2001 |
| Noise reduction for noise robust feature extraction for distributed speech recognition B Noé, J Sienel, D Jouvet, L Mauuary, J Veth, L Boves, F Wet Seventh European Conference on Speech Communication and Technology, 2001 | 18 | 2001 |
| Quality measurements for mobile data collection in the developing world J Badenhorst, A Waal, F Wet Spoken Language Technologies for Under-Resourced Languages, 2012 | 17 | 2012 |
| Automatically assessing the oral proficiency of proficient L2 speakers P Müller, F Wet, C Walt, T Niesler International Workshop on Speech and Language Technology in Education, 2009 | 17 | 2009 |
| Additive background noise as a source of non-linear mismatch in the cepstral and log-energy domain F de Wet, J de Veth, L Boves, B Cranen Computer Speech & Language 19 (1), 31-54, 2005 | 17 | 2005 |
| Feature vector selection to improve ASR robustness in noisy conditions J Veth, L Mauuary, B Noe, F Wet, J Sienel, L Boves, D Jouvet Seventh European Conference on Speech Communication and Technology, 2001 | 17 | 2001 |
| Pronunciation modelling of foreign words for Sepedi ASR T Modipa, MH Davel PRASA 2010, 2010 | 16 | 2010 |
| Multilingual Neural Network Acoustic Modelling for ASR of Under-Resourced English-isiZulu Code-Switched Speech. A Biswas, F de Wet, E van der Westhuizen, E Yilmaz, T Niesler Interspeech, 2603-2607, 2018 | 15 | 2018 |
Thomas NieslerDepartment of Electrical and Electronic Engineering, University of Stellenbosch, South AfricaVerified email at sun.ac.za
