| 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 | 220 | 2007 |
| The Voice Conversion Challenge 2016. T Toda, LH Chen, D Saito, F Villavicencio, M Wester, Z Wu, J Yamagishi Interspeech, 1632-1636, 2016 | 130 | 2016 |
| 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 | 127 | 2015 |
| Articulatory feature recognition using dynamic Bayesian networks J Frankel, M Wester, S King Computer Speech & Language 21 (4), 620-640, 2007 | 126 | 2007 |
| 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 | 105 | 1999 |
| Pronunciation modeling for ASR–knowledge-based and data-derived methods M Wester Computer Speech & Language 17 (1), 69-85, 2003 | 89 | 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 24 (4), 768-783, 2016 | 70 | 2016 |
| An elitist approach to articulatory-acoustic feature classification S Chang, S Greenberg, M Wester Seventh European Conference on Speech Communication and Technology, 2001 | 50 | 2001 |
| Talker discrimination across languages M Wester Speech Communication 54 (6), 781-790, 2012 | 47 | 2012 |
| Analysis of the Voice Conversion Challenge 2016 Evaluation Results. M Wester, Z Wu, J Yamagishi Interspeech, 1637-1641, 2016 | 44 | 2016 |
| Asynchronous articulatory feature recognition using dynamic Bayesian networks M Wester, J Frankel, S King | 41 | 2004 |
| Syllable classification using articulatory-acoustic features M Wester Eighth European Conference on Speech Communication and Technology, 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 | 38 | 2001 |
| 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 | 36 | 2016 |
| The EMIME bilingual database M Wester The University of Edinburgh, 2010 | 35 | 2010 |
| A comparison of data-derived and knowledge-based modeling of pronunciation variation M Wester, E Fosler-Lussier Sixth International Conference on Spoken Language Processing, 2000 | 34 | 2000 |
| Automatic classification of voice quality: comparing regression models and hidden Markov models M Wester Utrecht Institute of Linguistics OTS, 1998 | 34 | 1998 |
| Improving the performance of a Dutch CSR by modeling pronunciation variation M Wester, JM Kessens, H Strik Nijmegen: KU Nijmegen, 1998 | 33 | 1998 |
| 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 | 32 | 2005 |
| Are we using enough listeners? No!—an empirically-supported critique of Interspeech 2014 TTS evaluations M Wester, C Valentini-Botinhao, GE Henter Sixteenth Annual Conference of the International Speech Communication …, 2015 | 29 | 2015 |
Simon KingProfessor of Speech Processing, University of EdinburghAdresse e-mail validée de ed.ac.uk
