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[1]
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John Dines, Hui Liang, Lakshmi Saheer, Matthew Gibson, William Byrne, Keiichiro
Oura, Keiichi Tokuda, Junichi Yamagishi, Simon King, Mirjam Wester, Teemu
Hirsimäki, Reima Karhila, and Mikko Kurimo.
Personalising speech-to-speech translation: Unsupervised
cross-lingual speaker adaptation for HMM-based speech synthesis.
Computer Speech and Language, 27(2):420-437, February 2013.
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[2]
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Mirjam Wester.
Talker discrimination across languages.
Speech Communication, 54:781-790, 2012.
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[3]
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Martin Cooke, Maria Luisa García Lecumberri, Yan Tang, and Mirjam Wester.
Do non-native listeners benefit from speech modifications designed to
promote intelligibility for native listeners?
In Proceedings of The Listening Talker Workshop, page 59, 2012.
http://listening-talker.org/workshop/programme.html.
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[4]
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Keiichiro Oura, Junichi Yamagishi, Mirjam Wester, Simon King, and Keiichi
Tokuda.
Analysis of unsupervised cross-lingual speaker adaptation for
HMM-based speech synthesis using KLD-based transform mapping.
Speech Communication, 54(6):703-714, 2012.
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[5]
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Leonardo Badino, Robert A.J. Clark, and Mirjam Wester.
Towards hierarchical prosodic prominence generation in TTS
synthesis.
In Proc. Interspeech, Portland, USA, 2012.
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[6]
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Reima Karhila and Mirjam Wester.
Rapid adaptation of foreign-accented HMM-based speech synthesis.
In Proc. Interspeech, Florence, Italy, 2011.
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[7]
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Mirjam Wester and Hui Liang.
Cross-lingual speaker discrimination using natural and synthetic
speech.
In Proc. Interspeech, Florence, Italy, 2011.
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[8]
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Mirjam Wester and Reima Karhila.
Speaker similarity evaluation of foreign-accented speech synthesis
using HMM-based speaker adaptation.
In Proc. ICASSP, pages 5372-5375, Prague, Czech Republic,
2011.
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[9]
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Mirjam Wester and Hui Liang.
The EMIME Mandarin Bilingual Database.
Technical Report EDI-INF-RR-1396, The University of Edinburgh, 2011.
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[10]
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Mirjam Wester.
Cross-lingual talker discrimination.
In Proc. of Interspeech, Makuhari, Japan, September 2010.
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[11]
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Mirjam Wester, John Dines, Matthew Gibson, Hui Liang, Yi-Jian Wu, Lakshmi
Saheer, Simon King, Keiichiro Oura, Philip N. Garner, William Byrne, Yong
Guan, Teemu Hirsimäki, Reima Karhila, Mikko Kurimo, Matt Shannon, Sayaka
Shiota, Jilei Tian, Keiichi Tokuda, and Junichi Yamagishi.
Speaker adaptation and the evaluation of speaker similarity in the
EMIME speech-to-speech translation project.
In Proc. of 7th ISCA Speech Synthesis Workshop, Kyoto, Japan,
September 2010.
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[12]
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Mikko Kurimo, William Byrne, John Dines, Philip N. Garner, Matthew Gibson, Yong
Guan, Teemu Hirsimäki, Reima Karhila, Simon King, Hui Liang, Keiichiro
Oura, Lakshmi Saheer, Matt Shannon, Sayaka Shiota, Jilei Tian, Keiichi
Tokuda, Mirjam Wester, Yi-Jian Wu, and Junichi Yamagishi.
Personalising speech-to-speech translation in the EMIME project.
In Proc. of the ACL 2010 System Demonstrations, Uppsala,
Sweden, July 2010.
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[13]
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M. Wester.
The EMIME Bilingual Database.
Technical Report EDI-INF-RR-1388, The University of Edinburgh, 2010.
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[14]
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Keiichiro Oura, Keiichi Tokuda, Junichi Yamagishi, Mirjam Wester, and Simon
King.
Unsupervised cross-lingual speaker adaptation for HMM-based speech
synthesis.
In Proc. of ICASSP, volume I, pages 4954-4957, 2010.
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[15]
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J. Frankel, M. Wester, and S. King.
Articulatory feature recognition using dynamic Bayesian networks.
Computer Speech & Language, 21(4):620-640, October 2007.
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[16]
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S. King, J. Frankel, K. Livescu, E. McDermott, K. Richmond, and M. Wester.
Speech production knowledge in automatic speech recognition.
Journal of the Acoustical Society of America, 121(2):723-742,
February 2007.
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[17]
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S. Chang, M. Wester, and S. Greenberg.
An elitist approach to automatic articulatory-acoustic feature
classification for phonetic characterization of spoken language.
Speech Communication, 47:290-311, 2005.
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[18]
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M. Wester, J. Frankel, and S. King.
Asynchronous articulatory feature recognition using dynamic
Bayesian networks.
In Proc. IEICI Beyond HMM Workshop, Kyoto, December 2004.
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[19]
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J. Frankel, M. Wester, and S. King.
Articulatory feature recognition using dynamic Bayesian networks.
In Proc. ICSLP, September 2004.
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[20]
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Alexander Gutkin, David Gay, Lev Goldfarb, and Mirjam Wester.
On the Articulatory Representation of Speech within the
Evolving Transformation System Formalism.
In Lev Goldfarb, editor, Pattern Representation and the Future
of Pattern Recognition (Proc. Satellite Workshop of 17th International
Conference on Pattern Recognition), pages 57-76, Cambridge, UK, August
2004.
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[21]
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J. Sturm, J. M. Kessens, M. Wester, F. de Wet, E. Sanders, and H. Strik.
Automatic transcription of football commentaries in the MUMIS
project.
In Proc. Eurospeech '03, pages -, 2003.
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[22]
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M. Wester.
Syllable classification using articulatory-acoustic features.
In Proc. of Eurospeech '03, pages -, Geneva, 2003.
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[23]
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M. Wester.
Pronunciation modeling for ASR - knowledge-based and data-derived
methods.
Computer Speech and Language, 17:69-85, 2003.
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[24]
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M. Wester, J.M. Kessens, and H. Strik.
Goal-directed ASR in a multimedia indexing and searching
environment (MUMIS).
In Proc. of ICSLP, pages 1993-1996, Denver, 2002.
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[25]
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Mirjam Wester.
Pronunciation Variation Modeling for Dutch Automatic Speech
Recognition.
PhD thesis, University of Nijmegen, 2002.
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[26]
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M. Wester, J. M. Kessens, C. Cucchiarini, and H. Strik.
Obtaining phonetic transcriptions: a comparison between expert
listeners and a continuous speech recognizer.
Language and Speech, 44(3):377-403, 2001.
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[27]
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S. Chang, S. Greenberg, and M. Wester.
An elitist approach to articulatory-acoustic feature classification.
In Proc. of Eurospeech '01, pages 1729-1733, Aalborg, 2001.
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[28]
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M. Wester, S. Greenberg, and S. Chang.
A Dutch treatment of an elitist approach to articulatory-acoustic
feature classification.
In Proc. of Eurospeech '01, pages 1729-1732, Aalborg, 2001.
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[29]
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J.M. Kessens, M. Wester, and H. Strik.
Automatic detection and verification of Dutch phonological rules.
In PHONUS 5: Proceedings of the "Workshop on Phonetics and
Phonology in ASR", pages 117-128, Saarbruecken, 2000.
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[30]
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M. Wester, J.M. Kessens, and H. Strik.
Pronunciation variation in ASR: Which variation to model?
In Proc. of ICSLP '00, volume IV, pages 488-491, Beijing,
2000.
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[31]
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M. Wester and E. Fosler-Lussier.
A comparison of data-derived and knowledge-based modeling of
pronunciation variation.
In Proc. of ICSLP '00, volume I, pages 270-273, Beijing, 2000.
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[32]
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M. Wester, J.M. Kessens, and H. Strik.
Using Dutch phonological rules to model pronunciation variation in
ASR.
In Phonus 5: proceedings of the "workshop on phonetics and
phonology in ASR", pages 105-116, Saarbruecken, 2000.
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[33]
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J.M. Kessens, M. Wester, and H. Strik.
Improving the performance of a Dutch CSR by modeling within-word
and cross-word pronunciation variation.
Speech Communication, 29:193-207, 1999.
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[34]
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J.M. Kessens, M. Wester, and H. Strik.
Modeling within-word and cross-word pronunciation variation to
improve the performance of a Dutch CSR.
In Proc. of ICPhS '99, pages 1665-1668, San Francisco, 1999.
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[35]
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M. Wester and J.M. Kessens.
Comparison between expert listeners and continuous speech recognizers
in selecting pronunciation variants.
In Proc. of ICPhS '99, pages 723-726, San Francisco, 1999.
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[36]
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M. Wester, J.M. Kessens, C. Cucchiarini, and H. Strik.
Selection of pronunciation variants in spontaneous speech: Comparing
the performance of man and machine.
In Proc. of the ESCA Workshop on the Sound Patterns of
Spontaneous Speech: Production and Perception, pages 157-160,
Aix-en-Provence, 1998.
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[37]
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M. Wester, J.M. Kessens, and H. Strik.
Modeling pronunciation variation for a Dutch CSR: testing three
methods.
In Proc. ICSLP '98, pages 2535-2538, Sydney, 1998.
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[38]
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M. Wester, J.M. Kessens, and H. Strik.
Improving the performance of a Dutch CSR by modeling
pronunciation variation.
In Proc. of the Workshop Modeling Pronunciation Variation for
Automatic Speech Recognition, pages 145-150, Kerkrade, 1998.
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[39]
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M. Wester, J.M. Kessens, and H. Strik.
Two automatic approaches for analyzing the frequency of connected
speech processes in Dutch.
In Proc. ICSLP Student Day '98, pages 3351-3356, Sydney, 1998.
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[40]
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M. Wester.
Automatic classification of voice quality: Comparing regression
models and hidden Markov models.
In Proc. of VOICEDATA98, Symposium on Databases in Voice Quality
Research and Education, pages 92-97, Utrecht, 1998.
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[41]
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J.M. Kessens, M. Wester, C. Cucchiarini, and H. Strik.
The selection of pronunciation variants: Comparing the performance of
man and machine.
In Proc. of ICSLP '98, pages 2715-2718, Sydney, 1998.
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[42]
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J.M. Kessens and M. Wester.
Improving recognition performance by modelling pronunciation
variation.
In Proc. of the CLS opening Academic Year '97 '98, pages 1-20,
Nijmegen, 1997.
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[43]
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M. Wester, J.M. Kessens, C. Cucchiarini, and H. Strik.
Modelling pronunciation variation: some preliminary results.
In Proc. of the Dept. of Language & Speech, pages 127-137,
Nijmegen, 1997.
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[44]
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J.M. Kessens, M. Wester, C. Cucchiarini, and H. Strik.
Testing a method for modelling pronunciation variation.
In Proceedings of the COST workshop, pages 37-40, Rhodos,
1997.
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