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| LPC-based inversion of the DRM articulatory model, , in: Proc. Eurospeech'99, 1999 |
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| Acoustico-articulatory inversion of unequal-length tube models through lattice inverse filtering, , Idiap-RR-16-1998 |
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| Investigation of a possible process identity between DRM and Linear Filtering, , Idiap-RR-19-1997 |
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| Présentation du Modèle DRM, , Idiap-Com-03-1996 |
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| Signal modeling with Non Uniform Topology lattice filters, and , in: Proc. ICASSP 2001, 2001 |
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| Inverse lattice filtering of speech with adapted non-uniform delays, and , in: Proc. ICSLP 2000, 2000 |
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| On the Vulnerability of Speaker Verification to Realistic Voice Spoofing, , , and , in: IEEE International Conference on Biometrics: Theory, Applications and Systems, pages 1-8, IEEE, 2015 |
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| Learning strategies and representations for intuitive robot learning from demonstration, , EPFL, 2021 |
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| Combining Social and Intrinsically-Motivated Learning for Multi-Task Robot Skill Acquisition, and , in: IEEE Transactions on Cognitive and Developmental Systems, 15(2):385-394, 2023 |
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| Intrinsically-Motivated Robot Learning of Bayesian Probabilistic Movement Primitives, and , in: ICRA workshop: "Towards Curious Robots: Modern Approaches for Intrinsically-Motivated Intelligent Behavior", 2021 |
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| Active Learning of Bayesian Probabilistic Movement Primitives, , , and , in: IEEE Robotic and Automation Letters, 2021 |
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| Fourier movement primitives: an approach for learning rhythmic robot skills from demonstrations, , and , in: Robotics: Science and Systems, 2020 |
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| Unveiling Biases while Embracing Sustainability: Assessing the Dual Challenges of Automatic Speech Recognition Systems, , , and , in: ISCA proceedings, Greece, pages 4, 2024 |
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| Exploring generalization to unseen audio data for spoofing: insights from SSL models, , , , , and , in: ISCA Proceedings, Greece, 2024 |
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| Modelling glottal source information for depression detection, , and , Idiap-RR-13-2018 |
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| Multitask Speech Recognition and Speaker Change Detection for Unknown Number of Speakers, , , , , , , and , in: Proceedings of the 49th IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP) 2024, Seoul, Republic of Korea, pages 12592-12596, IEEE, 2024 |
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| TokenVerse: Unifying Speech and NLP Tasks via Transducer-based ASR, , , , , , , , and , Idiap-RR-07-2024 |
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| TokenVerse: Towards Unifying Speech and NLP Tasks via Transducer-based ASR, , , , , , , , and , in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 20988–20995, Association for Computational Linguistics (ACL), 2024 |
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| XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models, , , , , , , and , Idiap-RR-08-2024 |
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| Minimum Mutual Information Beamforming for Simultaneous Active Speakers, , , , , and , Idiap-RR-73-2007 |
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| Adaptive Beamforming with a Minimum Mutual Information Criterion, , , , , and , Idiap-RR-74-2007 |
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| Adaptive Beamforming with a Maximum Negentropy Criterion, , , , and , Idiap-RR-06-2008 |
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| Maximum Negentropy Beamforming, , , , and , Idiap-RR-07-2008 |
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| Adaptive Beamforming with a Maximum Negentropy Criterion, , , , and , in: Proceedings of the Joint Workshop on Hands-free Speech Communication and Microphone Arrays, Italy, 2008 |
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| Adaptive Beamforming with a Maximum Negentropy Criterion, , , , , and , Idiap-RR-29-2008 |
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| Maximum kurtosis beamforming with the generalized sidelobe canceller, , , , , and , in: Proceedings of INTERSPEECH, September 2008, Brisbane, Australia, 2008 |
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| Beamforming with a Maximum Negentropy Criterion, , , , , and , in: IEEE Transactions on Audio Speech and Language Processing, 17(5), 2009 |
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| Filter Bank Design for Subband Adaptive Beamforming and Application to Speech Recognition, , , , , and , Idiap-RR-02-2008 |
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| Filter Bank Design based on Minimization of Individual Aliasing Terms for Minimum Mutual Information Subband Adaptive Beamforming, , , , , and , in: Proceedings of ICASSP 2008, Las Vegas, USA, 2008 |
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| Filter Bank Design based on Minimization of Individual Aliasing Terms for Minimum Mutual Information Subband Adaptive Beamforming, , , , , and , Idiap-RR-77-2007 |
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| Fast latent semantic indexing of spoken documents by using self-organizing maps, , in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP'2000, 2000 |
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| Indexing spoken audio by LSA and SOMs, , in: Proceedings of the European Signal Processing Conference EUSIPCO'2000, 2000 |
| Thematic Indexing of Spoken Documents by Using Self-Organizing Maps, , Idiap-RR-05-2000 |
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| Indexing spoken audio by LSA and SOMs, , Idiap-RR-06-2000 |
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| Fast latent semantic indexing of spoken documents by using self-organizing maps, , Idiap-RR-20-1999 |
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| Indexing Audio Documents by using Latent Semantic Analysis and SOM, , Idiap-RR-13-1999 |
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| Personalising speech-to-speech translation in the EMIME project, , , , , , , , , , , , , , , , , , and , in: Proceedings of the ACL 2010 System Demonstrations, Association for Computational Linguistics, Uppsala, Sweden, 2010 |
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| Latent Semantic Indexing by Self-Organizing Map, and , in: ESCA ETRW workshop on Accessing Information in Spoken Audio, 1999 |
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| Latent Semantic Indexing by Self-Organizing Map, and , Idiap-RR-12-1999 |
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| Indexing Audio Documents by using Latent Semantic Analysis and SOM, , in: Kohonen Maps, Elsevier, 1999 |
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| Theory and Algorithms for Hypothesis Transfer Learning, , EPFL, 2018 |
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| When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks, , and , in: Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2016 |
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| On the Challenge of Classifying 52 Hand Movements from Surface Electromyography, , and , in: 34th Annual Conference of the IEEE Engineering in Medicine & Biology Society, 2012 |
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| Fast Rates by Transferring from Auxiliary Hypotheses, and , in: Machine Learning, 2016 |
| Stability and Hypothesis Transfer Learning, and , in: International Conference on Machine Learning, 2013 |
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| Scalable greedy algorithms for transfer learning, , and , in: Computer Vision and Image Understanding, 2016 |
| Transfer Learning through Greedy Subset Selection, , and , Idiap-RR-26-2015 |
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| Transfer Learning through Greedy Subset Selection, , and , in: Image Analysis and Processing - ICIAP 2015, Genoa, Italy, pages 3-14, Springer International Publishing, 2015 |
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| From N to N+1: Multiclass Transfer Incremental Learning, , and , in: Proceedings of the Conference on Computer Vision and Pattern Recognition, 2013 |
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| Context is Everything: Using a Smartphone App to Capture Young People's Drinking Behaviours, Cognitions, Environments, and Consequences, , La Trobe University, Melbourne, Australia, 2020 |
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