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 Strikco-founder and CSO NovoLanguage, Associate Professor Radboud University, PI Centre for LanguageVerified email at let.ru.nl
Zhizheng WuFBVerified email at zhizheng.org
Keiichi TokudaNagoya Institute of TechnologyVerified email at nitech.ac.jp
Rasmus DallJibo Inc.Verified email at dall.dk
Gustav Eje HenterKTH Royal Institute of Technology, Stockholm, SwedenVerified email at kth.se
Bill ByrneProfessor in Information Engineering, Cambridge UniversityVerified email at eng.cam.ac.uk
Reima KarhilaAalto UniversityVerified email at aalto.fi
Hui LIANGNuance Communications Deutschland GmbHVerified email at nuance.com
Korin RichmondCentre for Speech Technology Research, University of EdinburghVerified email at cstr.ed.ac.uk
Tomoki TodaNagoya UniversityVerified email at icts.nagoya-u.ac.jp
Cassia Valentini-BotinhaoUniversity of EdinburghVerified email at sms.ed.ac.uk
Matthew AylettCSO, CereProc Ltd., Honorary Fellow, University of EdinburghVerified email at inf.ed.ac.uk
Peter BellUniversity of EdinburghVerified email at ed.ac.uk
Steve RenalsProfessor of Speech Technology, University of EdinburghVerified email at ed.ac.uk
Mikko KurimoProfessor in Speech and Language Processing, Aalto University, FinlandVerified email at aalto.fi
John DinesPrincipal Data Scientist at Expedia, Inc.Verified email at expedia.com
Matthew GibsonVerified email at nuance.com
Pierre LanchantinLead Research Scientist in Speech TechnologyVerified email at transperfect.com

Mirjam Wester

IOHK & Research Fellow University of Edinburgh

Verified email at inf.ed.ac.uk

Automatic Speech Recognition Text-to-Speech Synthesis Human Speech Perception


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	226	2007
The Voice Conversion Challenge 2016. T Toda, LH Chen, D Saito, F Villavicencio, M Wester, Z Wu, J Yamagishi Interspeech, 1632-1636, 2016	137	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	136	2015
Articulatory feature recognition using dynamic Bayesian networks J Frankel, M Wester, S King Computer Speech & Language 21 (4), 620-640, 2007	129	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	106	1999
Pronunciation modeling for ASR–knowledge-based and data-derived methods M Wester Computer Speech & Language 17 (1), 69-85, 2003	91	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	72	2016
Analysis of the Voice Conversion Challenge 2016 Evaluation Results. M Wester, Z Wu, J Yamagishi Interspeech, 1637-1641, 2016	51	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	48	2012
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	39	2003
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	38	2016
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
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	31	2015

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