Febe de Wet
TitleCited byYear
Comparing different approaches for automatic pronunciation error detection
H Strik, K Truong, F de Wet, C Cucchiarini
Speech Communication 51 (10), 845-852, 2009
1472009
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
942014
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
532014
Comparing classifiers for pronunciation error detection
H Strik, KP Truong, F Wet, C Cucchiarini
Eighth Annual Conference of the International Speech Communication Association, 2007
422007
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
372009
Implications of Sepedi/English code switching for ASR systems
TI Modipa, MH Davel, F De Wet
PRASA 2013 Proceedings, 2013
342013
Assessment of Dutch pronunciation by means of automatic speech recognition technology
C Cucchiarini, F Wet, H Strik, LWJ Boves
Sydney:[sn], 1998
311998
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
29*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
271999
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
262005
Verifying pronunciation dictionaries using conflict analysis.
MH Davel, F de Wet
INTERSPEECH, 1898-1901, 2010
212010
The origin of Afrikaans pronunciation: a comparison to west Germanic languages and Dutch dialects
W Heeringa, F De Wet
Proc. Conference of the Pattern Recognition Association of South Africa, 159-164, 2008
182008
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
182001
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
182001
Quality measurements for mobile data collection in the developing world
J Badenhorst, A Waal, F Wet
Spoken Language Technologies for Under-Resourced Languages, 2012
172012
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
172001
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
162009
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
162005
Pronunciation modelling of foreign words for Sepedi ASR
T Modipa, MH Davel
PRASA 2010, 2010
142010
ASR-based pronunciation training: Scoring accuracy and pedagogical effectiveness of a system for Dutch L2 learners
C Cucchiarini, A Neri, F Wet, H Strik
Eighth Annual Conference of the International Speech Communication Association, 2007
142007
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