Mirjam Wester

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Simon KingProfessor of Speech Processing, University of EdinburghVerified email at ed.ac.uk
Junichi YamagishiNational Institute of Informatics, Tokyo, JapanVerified email at nii.ac.jp
Helmer StrikPI, Associate Professor Radboud University, co-founder and CSO NovoLanguageVerified email at let.ru.nl
Zhizheng WuChinese University of Hong Kong, Shenzhen, Mel LabVerified email at cuhk.edu.cn
Keiichi TokudaNagoya Institute of TechnologyVerified email at nitech.ac.jp
Gustav Eje HenterKTH Royal Institute of Technology, Stockholm, SwedenVerified email at kth.se
Rasmus DallSpotify Inc.Verified email at dall.dk
Bill ByrneProfessor of Information Engineering, Cambridge UniversityVerified email at eng.cam.ac.uk
Reima KarhilaAalto UniversityVerified email at silo.ai
Tomoki TodaNagoya UniversityVerified email at icts.nagoya-u.ac.jp
Cassia Valentini-BotinhaoUniversity of EdinburghVerified email at inf.ed.ac.uk
Matthew AylettAssociate Professor, Heriot Watt University, CSO, CereProc Ltd.Verified email at hw.ac.uk
John DinesDirector Machine Learning Science at Expedia GroupVerified email at expedia.com
Mikko KurimoProfessor in Speech and Language Processing, Aalto University, FinlandVerified email at aalto.fi
Matthew GibsonVerified email at nuance.com
Korin RichmondCentre for Speech Technology Research, University of EdinburghVerified email at cstr.ed.ac.uk
Peter BellUniversity of EdinburghVerified email at ed.ac.uk
Steve RenalsUniversity of EdinburghVerified email at ed.ac.uk
Pierre LanchantinLead Research Scientist in Speech TechnologyVerified email at transperfect.com
Hui LIANGNIO GmbH

Mirjam Wester

IOHK & University of Edinburgh

Verified email at inf.ed.ac.uk


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	247	2007
The Voice Conversion Challenge 2016. T Toda, LH Chen, D Saito, F Villavicencio, M Wester, Z Wu, J Yamagishi Interspeech, 1632-1636, 2016	208	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	181	2015
Articulatory feature recognition using dynamic Bayesian networks J Frankel, M Wester, S King Computer Speech & Language 21 (4), 620-640, 2007	133	2007
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	114	2016
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	106	1999
Pronunciation modeling for ASR–knowledge-based and data-derived methods M Wester Computer Speech & Language 17 (1), 69-85, 2003	96	2003
Analysis of the Voice Conversion Challenge 2016 Evaluation Results. M Wester, Z Wu, J Yamagishi Interspeech, 1637-1641, 2016	86	2016
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	78	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	62	2015
Talker discrimination across languages M Wester Speech Communication 54 (6), 781-790, 2012	57	2012
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	48	2016
The EMIME bilingual database M Wester The University of Edinburgh, 2010	45	2010
Asynchronous articulatory feature recognition using dynamic Bayesian networks M Wester, J Frankel, S King	41	2004
Syllable classification using articulatory-acoustic features M Wester International Speech Communication Association, 2003	39	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	39	2001
Automatic classification of voice quality: comparing regression models and hidden Markov models M Wester Utrecht Institute of Linguistics OTS, 1998	37	1998
A comparison of data-derived and knowledge-based modeling of pronunciation variation M Wester, E Fosler-Lussier International Speech Communication Association, 2000	36	2000
Human vs machine spoofing detection on wideband and narrowband data M Wester, Z Wu, J Yamagishi Sixteenth annual conference of the international speech communication …, 2015	35	2015
Speech synthesis for the generation of artificial personality MP Aylett, A Vinciarelli, M Wester IEEE transactions on affective computing 11 (2), 361-372, 2017	34	2017

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