Speech production knowledge in automatic speech recognition S King, J Frankel, K Livescu, E McDermott, K Richmond, M Wester The Journal of the Acoustical Society of America 121 (2), 723-742, 2007 | 207 | 2007 |
Articulatory feature recognition using dynamic Bayesian networks J Frankel, M Wester, S King Computer Speech & Language 21 (4), 620-640, 2007 | 121 | 2007 |
The MGB challenge: Evaluating multi-genre broadcast media recognition P Bell, MJF Gales, T Hain, J Kilgour, P Lanchantin, X Liu, A McParland, ... 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015 | 114 | 2015 |
Improving the performance of a Dutch CSR by modeling within-word and cross-word pronunciation variation JM Kessens, M Wester, H Strik Speech Communication 29 (2-4), 193-207, 1999 | 103 | 1999 |
The Voice Conversion Challenge 2016. T Toda, LH Chen, D Saito, F Villavicencio, M Wester, Z Wu, J Yamagishi Interspeech, 1632-1636, 2016 | 101 | 2016 |
Pronunciation modeling for ASR–knowledge-based and data-derived methods M Wester Computer Speech & Language 17 (1), 69-85, 2003 | 88 | 2003 |
Anti-spoofing for text-independent speaker verification: An initial database, comparison of countermeasures, and human performance Z Wu, PL De Leon, C Demiroglu, A Khodabakhsh, S King, ZH Ling, ... IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 24 (4 …, 2016 | 49 | 2016 |
An elitist approach to articulatory-acoustic feature classification S Chang, S Greenberg, M Wester International Speech Communication Association, 2001 | 49 | 2001 |
Talker discrimination across languages M Wester Speech Communication 54 (6), 781-790, 2012 | 43 | 2012 |
Asynchronous articulatory feature recognition using dynamic Bayesian networks M Wester, J Frankel, S King | 39 | 2004 |
Syllable classification using articulatory-acoustic features M Wester International Speech Communication Association, 2003 | 38 | 2003 |
Obtaining phonetic transcriptions: A comparison between expert listeners and a continuous speech recognizer M Wester, JM Kessens, C Cucchiarini, H Strik Language and Speech 44 (3), 377-403, 2001 | 37 | 2001 |
A comparison of data-derived and knowledge-based modeling of pronunciation variation M Wester, E Fosler-Lussier International Speech Communication Association, 2000 | 35 | 2000 |
Automatic classification of voice quality: comparing regression models and hidden Markov models M Wester Utrecht Institute of Linguistics OTS, 1998 | 35 | 1998 |
Analysis of the Voice Conversion Challenge 2016 Evaluation Results. M Wester, Z Wu, J Yamagishi Interspeech, 1637-1641, 2016 | 33 | 2016 |
Improving the performance of a Dutch CSR by modeling pronunciation variation M Wester, JM Kessens, H Strik Nijmegen: KU Nijmegen, 1998 | 33 | 1998 |
Robust TTS duration modelling using DNNs GE Henter, S Ronanki, O Watts, M Wester, Z Wu, S King 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 31 | 2016 |
The EMIME bilingual database M Wester The University of Edinburgh, 2010 | 31 | 2010 |
An elitist approach to automatic articulatory-acoustic feature classification for phonetic characterization of spoken language S Chang, M Wester, S Greenberg Speech Communication 47 (3), 290-311, 2005 | 30 | 2005 |
Speaker adaptation and the evaluation of speaker similarity in the EMIME speech-to-speech translation project M Wester, J Dines, M Gibson, H Liang, YJ Wu, L Saheer, S King, K Oura, ... | 27 | 2010 |