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Eric Joanis
Eric Joanis
Research Council Officer, National Research Council Canada
Dirección de correo verificada de cnrc-nrc.gc.ca
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A general feature space for automatic verb classification
E Joanis, S Stevenson, D James
Natural Language Engineering 14 (3), 337-367, 2008
1602008
Tightly packed tries: How to fit large models into memory, and make them load fast, too
U Germann, E Joanis, S Larkin
Proceedings of the Workshop on Software Engineering, Testing, and Quality …, 2009
622009
Semi-supervised verb class discovery using noisy features
S Stevenson, E Joanis
Proceedings of the Seventh Conference on Natural Language Learning at HLT …, 2003
532003
The Nunavut Hansard Inuktitut–English parallel corpus 3.0 with preliminary machine translation results
E Joanis, R Knowles, R Kuhn, S Larkin, P Littell, C Lo, D Stewart, J Micher
Proceedings of the Twelfth Language Resources and Evaluation Conference …, 2020
432020
Automatic verb classification using a general feature space
E Joanis
Master's thesis, Department of Computer Science, University of Toronto, 2002
322002
Lessons from NRC’s Portage System at WMT 2010
S Larkin, B Chen, G Foster, U Germann, E Joanis, H Johnson, R Kuhn
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation …, 2010
212010
The Indigenous Languages Technology Project at NRC Canada: an empowerment-oriented approach to developing language software (long version)
R Kuhn, F Davis, A Désilets, E Joanis, A Kazantseva, R Knowles, P Littell, ...
https://doi.org/10.4224/40001304, 2020
19*2020
Integration of an Arabic transliteration module into a statistical machine translation system
MM Kashani, E Joanis, R Kuhn, G Foster, F Popowich
Proceedings of the Second Workshop on Statistical Machine Translation, 17-24, 2007
142007
Portage: with smoothed phrase tables and segment choice models
H Johnson, F Sadat, G Foster, R Kuhn, M Simard, E Joanis, S Larkin
Proceedings on the Workshop on Statistical Machine Translation, 134-137, 2006
142006
Coarse “split and lump” bilingual language models for richer source information in SMT
D Stewart, R Kuhn, E Joanis, G Foster
Proceedings of the 11th Conference of the Association for Machine …, 2014
102014
Segment choice models: Feature-rich models for global distortion in statistical machine translation
R Kuhn, D Yuen, M Simard, P Paul, G Foster, E Joanis, H Johnson
Proceedings of the Human Language Technology Conference of the NAACL, Main …, 2006
92006
Transferring Markup Tags in Statistical Machine Translation: A Two-Stream Approach
E Joanis, D Stewart, S Larkin, R Kuhn
Machine Translation Summit XIV, 73, 2013
82013
Improving parallel data identification using iteratively refined sentence alignments and bilingual mappings of pre-trained language models
C Lo, E Joanis
Proceedings of the Fifth Conference on Machine Translation, 972-978, 2020
72020
Gi2Pi Rule-based, index-preserving grapheme-to-phoneme transformations
A Pine, PW Littell, E Joanis, DH Daines, C Cox, F Davis, EA Santos, ...
Proceedings of the Fifth Workshop on the Use of Computational Methods in the …, 2022
52022
PORTAGE in the NIST 2009 MT Evaluation
G Foster, B Chen, E Joanis, H Johnson, R Kuhn, S Larkin
NRC-CNRC, Tech. Rep, 2009
42009
ReadAlong Studio: Practical Zero-Shot Text-Speech Alignment for Indigenous Language Audiobooks
P Littell, E Joanis, A Pine, M Tessier, D Huggins-Daines, D Torkornoo
SIGUL2022 @LREC2022, 23–32, 2022
32022
Manageable phrase-based statistical machine translation models
G Badr, E Joanis, S Larkin, R Kuhn
Computer Recognition Systems 2, 437-444, 2008
32008
Review of the literature on aggregation in natural language generation
EJS Joanis
Technical Report CSRG-398, Department of Computer Science, University of …, 1999
31999
A general feature space for automatic verb classification
E Joanis, S Stevenson
Proceedings of the Tenth Conference of the EACL (EACL-03), 2003
12003
ReadAlong Studio Web Interface for Digital Interactive Storytelling
A Pine, DH Daines, E Joanis, P Littell, M Tessier, D Torkornoo, R Knowles, ...
Proceedings of the 18th Workshop on Innovative Use of NLP for Building …, 2023
2023
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