| Generative and discriminative algorithms for spoken language understanding C Raymond, G Riccardi Interspeech 2007-8th Annual Conference of the International Speech …, 2007 | 398 | 2007 |
| Comparing stochastic approaches to spoken language understanding in multiple languages S Hahn, M Dinarelli, C Raymond, F Lefevre, P Lehnen, R De Mori, ... IEEE Transactions on Audio, Speech, and Language Processing 19 (6), 1569-1583, 2010 | 147 | 2010 |
| On the use of finite state transducers for semantic interpretation C Raymond, F Bechet, R De Mori, G Damnati Speech Communication 48 (3-4), 288-304, 2006 | 82 | 2006 |
| Is it time to switch to Word Embedding and Recurrent Neural Networks for Spoken Language Understanding? V Vukotic, C Raymond, G Gravier Interspeech, 2015 | 63 | 2015 |
| One-step time-dependent future video frame prediction with a convolutional encoder-decoder neural network V Vukotić, SL Pintea, C Raymond, G Gravier, JC Van Gemert Image Analysis and Processing-ICIAP 2017: 19th International Conference …, 2017 | 62 | 2017 |
| Bidirectional joint representation learning with symmetrical deep neural networks for multimodal and crossmodal applications V Vukotić, C Raymond, G Gravier Proceedings of the 2016 ACM on International Conference on Multimedia …, 2016 | 56 | 2016 |
| Bidirectional deep architecture for Arabic speech recognition N Zerari, S Abdelhamid, H Bouzgou, C Raymond Open Computer Science 9 (1), 92-102, 2019 | 52 | 2019 |
| CRF-based combination of contextual features to improve a posteriori word-level confidence measures J Fayolle, F Moreau, C Raymond, G Gravier, P Gros Eleventh Annual Conference of the International Speech Communication Association, 2010 | 52 | 2010 |
| A step beyond local observations with a dialog aware bidirectional GRU network for Spoken Language Understanding V Vukotić, C Raymond, G Gravier Interspeech, 2016 | 45 | 2016 |
| A Comparison of Various Methods for Concept Tagging for Spoken Language Understanding. S Hahn, P Lehnen, C Raymond, H Ney LREC, 2008 | 43 | 2008 |
| Reconnaissance robuste d'entités nommées sur de la parole transcrite automatiquement C Raymond, J Fayolle Conférence Traitement automatique des langues naturelles, TALN'10, 2010 | 40 | 2010 |
| Multimodal and crossmodal representation learning from textual and visual features with bidirectional deep neural networks for video hyperlinking V Vukotić, C Raymond, G Gravier Proceedings of the 2016 ACM workshop on Vision and Language Integration …, 2016 | 38 | 2016 |
| Conceptual decoding from word lattices: application to the spoken dialogue corpus media C Servan, C Raymond, F Béchet, P Nocéra The Ninth International Conference on Spoken Language Processing …, 2006 | 37 | 2006 |
| Boosting bonsai trees for efficient features combination: application to speaker role identification A Laurent, N Camelin, C Raymond Interspeech, 2014 | 36 | 2014 |
| Is ATIS too shallow to go deeper for benchmarking Spoken Language Understanding models? F Béchet, C Raymond InterSpeech 2018, 1-5, 2018 | 30 | 2018 |
| Spoken language understanding with kernels for syntactic/semantic structures A Moschitti, G Riccardi, C Raymond 2007 IEEE workshop on automatic speech recognition & understanding (ASRU …, 2007 | 30 | 2007 |
| Conceptual decoding for spoken dialog systems. Y Esteve, C Raymond, F Béchet, R De Mori INTERSPEECH, 617-620, 2003 | 28 | 2003 |
| Bi-directional recurrent end-to-end neural network classifier for spoken Arab digit recognition N Zerari, S Abdelhamid, H Bouzgou, C Raymond Natural Language and Speech Processing (ICNLSP), 2018 2nd International …, 2018 | 27 | 2018 |
| Belief confirmation in spoken dialog systems using confidence measures C Raymond, Y Esteve, F Béchet, R De Mori, G Damnati 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE …, 2003 | 25 | 2003 |
| Benchmarking benchmarks: introducing new automatic indicators for benchmarking spoken language understanding corpora F Béchet, C Raymond Interspeech, 2019 | 23 | 2019 |
Renato De MoriMc Gill UniversityVerified email at cs.mcgill.ca
