F. D. Wet

发表

Automatic Speech Recognition in Adverse Acoustic Conditions

B. Cranen, F. D. Wet, J. D. Veth, 1999 .

Evaluation of formant-like features for automatic speech recognition 1

Samy Bengio, H. Bourlard, L. Boves, 2003 .

Proc. Eurospeech '03

Janienke Sturm, Helmer Strik, Eric Sanders, 2003 .

ASR-based pronunciation training : Scoring accuracy and pedagogical effectiveness of a system for Dutch L 2 learners 1 1 2 1

C. Cucchiarini, H. Strik, A. Neri, 2017 .

Additive background noise as a source of non-linear mismatch in the cepstral and log-energy domain

Lou Boves, Bert Cranen, Johan de Veth, 2005, Comput. Speech Lang..

HMM adaptation for child speech synthesis

Jules-Raymond Tapamo, Febe de Wet, Avashna Govender, 2015, INTERSPEECH.

Afrikaans and Dutch as closely-related languages: A comparison to West Germanic languages and Dutch dialects

Wilbert Heeringa, Febe de Wet, Gerhard B van Huyssteen, 2015 .

Comparing different approaches for automatic pronunciation error detection

Helmer Strik, Catia Cucchiarini, Khiet P. Truong, 2009, Speech Commun..

Comparing classifiers for pronunciation error detection

Helmer Strik, Catia Cucchiarini, Khiet P. Truong, 2007, INTERSPEECH.

Automatic detection of frequent pronunciation errors made by L2-learners

Helmer Strik, Catia Cucchiarini, Khiet P. Truong, 2005, INTERSPEECH.

Multilingual Bottleneck Features for Improving ASR Performance of Code-Switched Speech in Under-Resourced Languages

T. Niesler, F. D. Wet, E. V. D. Westhuizen, 2020, ArXiv.

Assessment of dutch pronunciation by means of automatic speech recognition technology

Lou Boves, Helmer Strik, Catia Cucchiarini, 1998, ICSLP.

The NCHLT speech corpus of the South African languages

Etienne Barnard, Marelie H. Davel, Jaco Badenhorst, 2014, SLTU.

A smartphone-based ASR data collection tool for under-resourced languages

Alta de Waal, Etienne Barnard, Marelie H. Davel, 2014, Speech Commun..

Semi-supervised Development of ASR Systems for Multilingual Code-switched Speech in Under-resourced Languages

Thomas Niesler, Emre Yilmaz, Astik Biswas, 2020, LREC.

Multilingual Neural Network Acoustic Modelling for ASR of Under-Resourced English-isiZulu Code-Switched Speech

Thomas Niesler, Astik Biswas, Emre Yilmaz, 2018, INTERSPEECH.

Building a Unified Code-Switching ASR System for South African Languages

Thomas Niesler, Astik Biswas, Emre Yilmaz, 2018, INTERSPEECH.

Semi-supervised Acoustic Modelling for Five-lingual Code-switched ASR using Automatically-segmented Soap Opera Speech pdf

F. de Wet, E. van der Westhuizen, T. R. Niesler, 2020, SLTU.

Automatic speech recognition in adverse acoustic conditions

F. de Wet, F. D. Wet, 1999 .

The Usefulness of Imperfect Speech Data for ASR Development in Low-Resource Languages

Jaco Badenhorst, Febe de Wet, J. Badenhorst, 2019, Inf..

Mathematical Content Browsing for Print-disabled Readers Based on Virtual-world Exploration and Audio-visual Sensory Substitution

T. Niesler, F. D. Wet, Febe de Wet, 2022, ACM Trans. Access. Comput..

Accent identification in the presence of code-mixing

Thomas Niesler, Febe de Wet, T. Niesler, 2008, Odyssey.

Code-switched automatic speech recognition in five South African languages

Ewald Van der Westhuizen, T. Niesler, Emre Yilmaz, 2018, Comput. Speech Lang..

A mobile vocabulary acquisition application for health science students: a proposed study

Febe de Wet, Elsabé Taljard, Ilana Wilken, 2015, LTLT@SLaTE.

Implications of Sepedi/English code switching for ASR systems

Marelie H. Davel, Febe de Wet, Thipe I. Modipa, 2013 .

Human and automatic accent identification of Nguni and Sotho Black South African English

Thomas Niesler, Febe de Wet, Philippa H. Louw, 2007 .

ASR-based pronunciation training: scoring accuracy and pedagogical effectiveness of a system for dutch L2 learners

Helmer Strik, Catia Cucchiarini, Febe de Wet, 2007, INTERSPEECH.

Speech data collection in an under-resourced language within a multilingual context

Etienne Barnard, Febe de Wet, Raymond Molapo, 2014, SLTU.

A distributed approach to speech resource collection

Etienne Barnard, Febe de Wet, Raymond Molapo, 2013 .

Verifying pronunciation dictionaries using conflict analysis

Marelie H. Davel, Febe de Wet, Marelie Hattingh Davel, 2010, INTERSPEECH.

Feature vector selection to improve ASR robustness in noisy conditions

Lou Boves, Denis Jouvet, Johan de Veth, 2001, INTERSPEECH.

Accumulated kullback divergence for analysis of ASR performance in the presence of noise

Lou Boves, Bert Cranen, Johan de Veth, 2002, INTERSPEECH.

A comparison of LPC and FFT-based acoustic features for noise robust ASR

Lou Boves, Bert Cranen, Johan de Veth, 2001, INTERSPEECH.

Acoustic features and a distance measure that reduce the impact of training-test mismatch in ASR

Lou Boves, Bert Cranen, Johan de Veth, 2001, Speech Commun..

Comparing acoustic features for robust ASR in fixed and cellular network applications

Lou Boves, Bert Cranen, Johan de Veth, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

Using likelihood ratios to perform utterance verification in automatic pronunciation assessment

Lou Boves, Helmer Strik, Catia Cucchiarini, 1999, EUROSPEECH.

Acoustic pre-processing for optimal effectivity of missing feature theory

Bert Cranen, F. de Wet, J. M. de Veth, 1999, EUROSPEECH.

COM PARING ACOUSTIC FEATURES FOR ROBUST ASR IN FIXED AND CELLULAR NETW ORK APPLICATIONS

L. Boves, B. Cranen, F. D. Wet, 2017 .

MISSING FEATURE THEORY IN ASR: MAKE SURE YOU MISS THE RIGHT TYPE OF FEATURES

Bert Cranen, Louis Boves, F. de Wet, 1999 .

Interactive Image Exploration for Visually Impaired Readers using Audio-augmented Touch Gestures

T. Niesler, F. D. Wet, Rynhardt Kruger, 2020, 2020 24th International Conference Information Visualisation (IV).