[1]
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Matthew P. Aylett, Alessandro Vinciarelli, and Mirjam Wester.
Speech synthesis for the generation of artificial personality.
IEEE Transactions on Affective Computing, 2017.
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[2]
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Takenori Yoshimura, Gustav Eje Henter, Oliver Watts, Mirjam Wester, Junichi
Yamagishi, and Keiichi Tokuda.
A hierarchical predictor of synthetic speech naturalness using neural
networks.
In Interspeech 2016, pages 342-346. International Speech
Communication Association, September 2016.
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[3]
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Mirjam Wester, Oliver Watts, and Gustav Eje Henter.
Evaluating comprehension of natural and synthetic conversational
speech.
In Speech Prosody, volume 8, pages 736-740, Boston, MA, June
2016.
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[4]
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Gustav Eje Henter, Srikanth Ronanki, Oliver Watts, Mirjam Wester, Zhizheng Wu,
and Simon King.
Robust TTS duration modelling using DNNs.
In Proc. ICASSP, volume 41, pages 5130-5134, Shanghai, China,
March 2016.
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[5]
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Tomoki Toda, Ling-Hui Chen, Daisuke Saito, Fernando Villavicencio, Mirjam
Wester, Zhizheng Wu, and Junichi Yamagishi.
The voice conversion challenge 2016.
In Proc. Interspeech, 2016.
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[6]
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Mirjam Wester, Zhizheng Wu, and Junichi Yamagishi.
Analysis of the voice conversion challenge 2016 evaluation results.
In Proc. Interspeech, 2016.
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[7]
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Mirjam Wester, Zhizheng Wu, and Junichi Yamagishi.
Multidimensional scaling of systems in the voice conversion challenge
2016.
In Proc. Speech Synthesis Workshop 9, Sunnyvale, CA., 2016.
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[8]
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Rasmus Dall, Marcus Tomalin, and Mirjam Wester.
Synthesising Filled Pauses: Representation and Datamixing.
In Proc. SSW9, Cupertino, CA, USA, 2016.
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[9]
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Mirjam Wester, Cassia Valentini-Botinhao, and Gustav Eje Henter.
Are we using enough listeners? No! An empirically-supported critique
of Interspeech 2014 TTS evaluations.
In Proc. Interspeech, pages 3476-3480, Dresden, September
2015.
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[10]
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Mirjam Wester, Matthew Aylett, Marcus Tomalin, and Rasmus Dall.
Artificial personality and disfluency.
In Proc. Interspeech, Dresden, September 2015.
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[11]
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Mirjam Wester, Zhizheng Wu, and Junichi Yamagishi.
Human vs machine spoofing detection on wideband and narrowband data.
In Proc. Interspeech, Dresden, September 2015.
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[12]
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Mirjam Wester, M. Luisa Garcia Lecumberri, and Martin Cooke.
/u/-fronting in English speakers' L1 but not in their L2.
In Proc. ICPhS, Glasgow, August 2015.
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[13]
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Marcus Tomalin, Mirjam Wester, Rasmus Dall, Bill Byrne, and Simon King.
A lattice-based approach to automatic filled pause insertion.
In Proc. DiSS 2015, Edinburgh, August 2015.
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[14]
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Mirjam Wester, Martin Corley, and Rasmus Dall.
The temporal delay hypothesis: Natural, vocoded and synthetic speech.
In Proc. DiSS 2015, Edinburgh, August 2015.
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[15]
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Rasmus Dall, Mirjam Wester, and Martin Corley.
Disfluencies in change detection in natural, vocoded and synthetic
speech.
In Proc. DiSS 2015, Edinburgh, August 2015.
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[16]
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Peter Bell, Mark Gales, Thomas Hain, Jonathan Kilgour, Pierre Lanchantin,
Xunying Liu, Andrew McParland, Steve Renals, Oscar Saz, Mirjam Wester, and
Phil Woodland.
The MGB challenge: Evaluating multi-genre broadcast media
recognition.
In Proc. ASRU, 2015.
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[17]
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C. Valentini-Botinhao and M. Wester.
Using linguistic predictability and the Lombard effect to increase
the intelligibility of synthetic speech in noise.
In Proc. Interspeech, pages 2063-2067, Singapore, September
2014.
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[18]
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Mirjam Wester and Cassie Mayo.
Accent rating by native and non-native listeners.
In Proceedings of ICASSP, pages 7749-7753, Florence, Italy,
May 2014.
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[19]
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Rasmus Dall, Mirjam Wester, and Martin Corley.
The effect of filled pauses and speaking rate on speech comprehension
in natural, vocoded and synthetic speech.
In Proc. Interspeech, 2014.
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[20]
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Mirjam Wester, M. Luisa Garcia Lecumberri, and Martin Cooke.
DIAPIX-FL: A symmetric corpus of problem-solving dialogues in first
and second languages.
In Proc. Interspeech, 2014.
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[21]
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Rasmus Dall, Marcus Tomalin, Mirjam Wester, William Byrne, and Simon King.
Investigating automatic & human filled pause insertion for speech
synthesis.
In Proc. Interspeech, 2014.
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[22]
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Cassia Valentini-Botinhao, Mirjam Wester, Junichi Yamagishi, and Simon King.
Using neighbourhood density and selective SNR boosting to increase
the intelligibility of synthetic speech in noise.
In 8th ISCA Workshop on Speech Synthesis, pages 133-138,
Barcelona, Spain, August 2013.
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[23]
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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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[24]
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Mirjam Wester.
Talker discrimination across languages.
Speech Communication, 54:781-790, 2012.
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[25]
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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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[26]
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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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[27]
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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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[28]
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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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[29]
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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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[30]
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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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[31]
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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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[32]
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Mirjam Wester.
Cross-lingual talker discrimination.
In Proc. Interspeech, Makuhari, Japan, September 2010.
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[33]
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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. 7th ISCA Speech Synthesis Workshop, Kyoto, Japan,
September 2010.
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[34]
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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. ACL 2010 System Demonstrations, Uppsala, Sweden, July
2010.
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[35]
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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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[36]
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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. ICASSP, volume I, pages 4954-4957, 2010.
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[37]
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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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[38]
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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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[39]
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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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[40]
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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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[41]
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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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[42]
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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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[43]
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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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[44]
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M. Wester.
Syllable classification using articulatory-acoustic features.
In Proc. Eurospeech '03, pages -, Geneva, 2003.
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[45]
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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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[46]
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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. ICSLP, pages 1993-1996, Denver, 2002.
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[47]
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Mirjam Wester.
Pronunciation Variation Modeling for Dutch Automatic Speech
Recognition.
PhD thesis, University of Nijmegen, 2002.
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[48]
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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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[49]
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S. Chang, S. Greenberg, and M. Wester.
An elitist approach to articulatory-acoustic feature classification.
In Proc. Eurospeech '01, pages 1729-1733, Aalborg, 2001.
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[50]
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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. Eurospeech '01, pages 1729-1732, Aalborg, 2001.
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[51]
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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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[52]
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M. Wester, J.M. Kessens, and H. Strik.
Pronunciation variation in ASR: Which variation to model?
In Proc. ICSLP '00, volume IV, pages 488-491, Beijing, 2000.
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[53]
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M. Wester and E. Fosler-Lussier.
A comparison of data-derived and knowledge-based modeling of
pronunciation variation.
In Proc. ICSLP '00, volume I, pages 270-273, Beijing, 2000.
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[54]
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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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[55]
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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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[56]
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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. ICPhS '99, pages 1665-1668, San Francisco, 1999.
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[57]
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M. Wester and J.M. Kessens.
Comparison between expert listeners and continuous speech recognizers
in selecting pronunciation variants.
In Proc. ICPhS '99, pages 723-726, San Francisco, 1999.
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[58]
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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. ESCA Workshop on the Sound Patterns of Spontaneous
Speech: Production and Perception, pages 157-160, Aix-en-Provence, 1998.
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[59]
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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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[60]
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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. Workshop Modeling Pronunciation Variation for Automatic
Speech Recognition, pages 145-150, Kerkrade, 1998.
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[61]
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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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[62]
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M. Wester.
Automatic classification of voice quality: Comparing regression
models and hidden Markov models.
In Proc. VOICEDATA98, Symposium on Databases in Voice Quality
Research and Education, pages 92-97, Utrecht, 1998.
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[63]
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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. ICSLP '98, pages 2715-2718, Sydney, 1998.
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[64]
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J.M. Kessens and M. Wester.
Improving recognition performance by modelling pronunciation
variation.
In Proc. CLS opening Academic Year '97 '98, pages 1-20,
Nijmegen, 1997.
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[65]
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M. Wester, J.M. Kessens, C. Cucchiarini, and H. Strik.
Modelling pronunciation variation: some preliminary results.
In Proc. Dept. of Language & Speech, pages 127-137, Nijmegen,
1997.
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[66]
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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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