Подписаться
Febe de Wet
Febe de Wet
Research Associate, Stellenbosch University, South Africa
Подтвержден адрес электронной почты в домене sun.ac.za
Название
Процитировано
Процитировано
Год
Comparing different approaches for automatic pronunciation error detection
H Strik, K Truong, F de Wet, C Cucchiarini
Speech Communication 51 (10), 845-852, 2009
1862009
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
1432014
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
1062014
Implications of Sepedi/English code switching for ASR systems
TI Modipa, F de Wet, MH Davel
Proceedings of PRASA, 2013
612013
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
562009
Comparing classifiers for pronunciation error detection
H Strik, KP Truong, F de Wet, C Cucchiarini
Interspeech, Antwerp, Belgium, 2007
532007
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
40*2004
Assessment of Dutch pronunciation by means of automatic speech recognition technology
C Cucchiarini, F de Wet, H Strik, LWJ Boves
ICSLP, Sydney, Australia, 1998
391998
Automatic detection of frequent pronunciation errors made by L2-learners
KP Truong, A Neri, F de Wet, C Cucchiarini, H Strik
Interspeech, Lisbon, Portugal, 2005
302005
Missing feature theory in ASR: make sure you miss the right type of features
JM de Veth, F de Wet, B Cranen, LWJ Boves
NOKIA Workshop on Robust Methods for Speech Recognition in Adverse …, 1999
281999
Verifying pronunciation dictionaries using conflict analysis.
MH Davel, F de Wet
Interspeech, Makuhari, Chiba, Japan, 1898-1901, 2010
252010
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, Hyderabad, India, 2603-2607, 2018
242018
Automatically assessing the oral proficiency of proficient L2 speakers
P Müller, F de Wet, C van der Walt, T Niesler
International Workshop on Speech and Language Technology in Education, 2009
222009
Building a Unified Code-Switching ASR System for South African Languages
E Yılmaz, A Biswas, E van der Westhuizen, F de Wet, T Niesler
arXiv preprint arXiv:1807.10949, 2018
212018
ASR-based pronunciation training: Scoring accuracy and pedagogical effectiveness of a system for Dutch L2 learners
C Cucchiarini, A Neri, F de Wet, H Strik
Interspeech, Antwerp, Belgium, 2007
212007
The origin of Afrikaans pronunciation: a comparison to west Germanic languages and Dutch dialects
W Heeringa, F de Wet
Proceedings of PRASA, 159-164, 2008
202008
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
202005
Quality measurements for mobile data collection in the developing world
J Badenhorst, A de Waal, F de Wet
Proccedings of the 3rd Workshop on Spoken Language Technologies for Under …, 2012
192012
Capitalising on North American speech resources for the development of a South African English large vocabulary speech recognition system
H Kamper, F de Wet, T Hain, T Niesler
Computer Speech & Language 28 (6), 1255-1268, 2014
182014
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
В данный момент система не может выполнить эту операцию. Повторите попытку позднее.
Статьи 1–20