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2020 – today
- 2024
[j8]Etienne Labbé
, Thomas Pellegrini, Julien Pinquier:
CoNeTTE: An Efficient Audio Captioning System Leveraging Multiple Datasets With Task Embedding. IEEE ACM Trans. Audio Speech Lang. Process. 32: 3785-3794 (2024)- [c67]Adrien Lafore, Clément Pagés, Leila Moudjari, Sebastião Quintas, Hervé Bredin, Thomas Pellegrini, Farah Benamara, Isabelle Ferrané, Jérôme Bertrand, Marie-Françoise Bertrand, Véronique Moriceau, Jérôme Farinas:
IRIT-MFU Multi-modal systems for emotion classification for Odyssey 2024 challenge. Odyssey 2024: 296-302 - [c66]Lucas Block Medin, Lucile Gelin, Thomas Pellegrini:
Adaptation de modèles auto-supervisés pour la reconnaissance de phonèmes dans la parole d'enfant. TALN (JEP) 2024: 231-241 - [c65]Adrien Lafore, Clément Pagés, Leila Moudjari, Sebastião Quintas, Isabelle Ferrané, Hervé Bredin, Thomas Pellegrini, Farah Benamara, Jérôme Bertrand, Marie-Françoise Bertrand, Véronique Moriceau, Jérôme Farinas:
Premier système IRIT-MyFamillyUp pour la compétition sur la reconnaissance des émotions Odyssey 2024. TALN (JEP) 2024: 502-511 - [i22]Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini:
CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System. CoRR abs/2406.17788 (2024) - [i21]Sebastião Quintas, Isabelle Ferrané, Thomas Pellegrini:
Enhancing Synthetic Training Data for Speech Commands: From ASR-Based Filtering to Domain Adaptation in SSL Latent Space. CoRR abs/2409.12745 (2024) - 2023
- [j7]Lionel Pibre, Francisco Madrigal, Cyrille Equoy, Frédéric Lerasle, Thomas Pellegrini, Julien Pinquier, Isabelle Ferrané:
Audio-video fusion strategies for active speaker detection in meetings. Multim. Tools Appl. 82(9): 13667-13688 (2023) - [c64]Etienne Labbé, Julien Pinquier, Thomas Pellegrini:
Multitask Learning in Audio Captioning: A Sentence Embedding Regression Loss Acts as a Regularizer. EUSIPCO 2023: 760-764 - [c63]Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier:
Dilated convolution with learnable spacings. ICLR 2023 - [c62]Thomas Pellegrini, Ismail Khalfaoui Hassani, Etienne Labbé, Timothée Masquelier:
Adapting a ConvNeXt Model to Audio Classification on AudioSet. INTERSPEECH 2023: 4169-4173 - [c61]Lucile Gelin, Morgane Daniel, Thomas Pellegrini, Julien Pinquier:
Comparing phoneme recognition systems on the detection and diagnosis of reading mistakes for young children's oral reading evaluation. SLaTE 2023: 6-10 - [i20]Etienne Labbé, Julien Pinquier, Thomas Pellegrini:
Multitask learning in Audio Captioning: a sentence embedding regression loss acts as a regularizer. CoRR abs/2305.01482 (2023) - [i19]Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier:
Dilated Convolution with Learnable Spacings: beyond bilinear interpolation. CoRR abs/2306.00817 (2023) - [i18]Thomas Pellegrini, Ismail Khalfaoui Hassani, Etienne Labbé, Timothée Masquelier:
Adapting a ConvNeXt model to audio classification on AudioSet. CoRR abs/2306.00830 (2023) - [i17]Etienne Labbé, Thomas Pellegrini, Julien Pinquier:
Killing two birds with one stone: Can an audio captioning system also be used for audio-text retrieval? CoRR abs/2308.15090 (2023) - [i16]Etienne Labbé, Thomas Pellegrini, Julien Pinquier:
CoNeTTE: An efficient Audio Captioning system leveraging multiple datasets with Task Embedding. CoRR abs/2309.00454 (2023) - [i15]Matéo Cousin, Etienne Labbé, Thomas Pellegrini:
Multilingual Audio Captioning using machine translated data. CoRR abs/2309.07615 (2023) - [i14]Ismail Khalfaoui Hassani, Timothée Masquelier, Thomas Pellegrini:
Audio classification with Dilated Convolution with Learnable Spacings. CoRR abs/2309.13972 (2023) - 2022
- [j6]Léo Cances, Etienne Labbé, Thomas Pellegrini:
Comparison of semi-supervised deep learning algorithms for audio classification. EURASIP J. Audio Speech Music. Process. 2022(1): 23 (2022) - [j5]Chems-Eddine Himeur, Thibault Lejemble, Thomas Pellegrini, Mathias Paulin, Loic Barthe, Nicolas Mellado:
PCEDNet: A Lightweight Neural Network for Fast and Interactive Edge Detection in 3D Point Clouds. ACM Trans. Graph. 41(1): 10:1-10:21 (2022) - [c60]Etienne Labbé, Thomas Pellegrini, Julien Pinquier:
Is my Automatic Audio Captioning System so Bad? SPIDEr-max: A Metric to Consider Several Caption Candidates. DCASE 2022 - [c59]Thomas Pellegrini:
Language-Based Audio Retrieval with Textual Embeddings of Tag Names. DCASE 2022 - [e1]Mathieu Lagrange, Annamaria Mesaros, Thomas Pellegrini, Gaël Richard, Romain Serizel, Dan Stowell:
Proceedings of the 7th Workshop on Detection and Classification of Acoustic Scenes and Events 2022, DCASE 2022, Nancy, France, November 3-4, 2022. Tampere University 2022, ISBN 978-952-03-2677-7 [contents] - [i13]Lionel Pibre, Francisco Madrigal, Cyrille Equoy, Frédéric Lerasle, Thomas Pellegrini, Julien Pinquier, Isabelle Ferrané:
Audio-video fusion strategies for active speaker detection in meetings. CoRR abs/2206.10411 (2022) - [i12]Etienne Labbé, Thomas Pellegrini, Julien Pinquier:
Is my automatic audio captioning system so bad? spider-max: a metric to consider several caption candidates. CoRR abs/2211.08983 (2022) - 2021
- [j4]Lucile Gelin, Morgane Daniel, Julien Pinquier, Thomas Pellegrini:
End-to-end acoustic modelling for phone recognition of young readers. Speech Commun. 134: 71-84 (2021) - [c58]Lionel Pibre, Sélim Mechrouh, Thomas Pellegrini, Julien Pinquier, Isabelle Ferrané:
Automatic macro segmentation into interaction sequence: a silence-based approach for meeting structuring. CBMI 2021: 1-4 - [c57]Lila Gravellier, Julie Hunter, Philippe Muller, Thomas Pellegrini, Isabelle Ferrané:
Weakly supervised discourse segmentation for multiparty oral conversations. EMNLP (1) 2021: 1381-1392 - [c56]Léo Cances, Thomas Pellegrini:
Comparison of Deep Co-Training and Mean-Teacher Approaches for Semi-Supervised Audio Tagging. ICASSP 2021: 361-365 - [c55]Thomas Pellegrini, Timothée Masquelier:
Fast Threshold Optimization for Multi-Label Audio Tagging Using Surrogate Gradient Learning. ICASSP 2021: 651-655 - [c54]Thomas Pellegrini:
Deep-Learning-Based Central African Primate Species Classification with MixUp and SpecAugment. Interspeech 2021: 456-460 - [c53]Lucile Gelin, Thomas Pellegrini, Julien Pinquier, Morgane Daniel:
Simulating Reading Mistakes for Child Speech Transformer-Based Phone Recognition. Interspeech 2021: 3860-3864 - [c52]Thomas Pellegrini, Romain Zimmer, Timothée Masquelier:
Low-Activity Supervised Convolutional Spiking Neural Networks Applied to Speech Commands Recognition. SLT 2021: 97-103 - [i11]Léo Cances, Etienne Labbé, Thomas Pellegrini:
Improving Deep-learning-based Semi-supervised Audio Tagging with Mixup. CoRR abs/2102.08183 (2021) - [i10]Thomas Pellegrini, Timothée Masquelier:
Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning. CoRR abs/2103.00833 (2021) - [i9]Lucile Gelin, Morgane Daniel, Julien Pinquier, Thomas Pellegrini:
End-to-end acoustic modelling for phone recognition of young readers. CoRR abs/2103.02899 (2021) - [i8]Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier:
Dilated convolution with learnable spacings. CoRR abs/2112.03740 (2021) - 2020
- [c51]Lucile Gelin, Morgane Daniel, Thomas Pellegrini, Julien Pinquier:
Reconnaissance de phones fondée sur du Transfer Learning pour des enfants apprenants lecteurs en environnement de classe (Transfer Learning based phone recognition on children learning to read, with speech recorded in a classroom environment). JEP-TALN-RECITAL (1) 2020: 253-261 - [c50]Cédric Gendrot, Emmanuel Ferragne, Thomas Pellegrini:
Informations segmentales pour la caractérisation phonétique du locuteur : variabilité inter- et intra-locuteurs (An automatic classification task involving 44 speakers was performed using convolutional neural networks (CNN) on broadband spectrograms extracted from 2-second sequences of a spontaneous speech corpus (NCCFr)). JEP-TALN-RECITAL (1) 2020: 262-270 - [c49]Thomas Pellegrini:
Deep learning with weakly-annotated data: a sound event detection use case (and hate speech detection here and there) (abstract). TWSDetection 2020: 31-32 - [i7]Chems-Eddine Himeur, Thibault Lejemble, Thomas Pellegrini, Mathias Paulin, Loic Barthe, Nicolas Mellado:
PCEDNet : A Neural Network for Fast and Efficient Edge Detection in 3D Point Clouds. CoRR abs/2011.01630 (2020) - [i6]Thomas Pellegrini, Romain Zimmer, Timothée Masquelier:
Low-activity supervised convolutional spiking neural networks applied to speech commands recognition. CoRR abs/2011.06846 (2020)
2010 – 2019
- 2019
- [c48]Jonathan Mamou, Thomas Pellegrini, Denis Kouamé, Adrian Basarab:
A Convolutional Neural Network for 250-MHz Quantitative Acoustic-microscopy Resolution Enhancement. EMBC 2019: 6212-6215 - [c47]Thomas Pellegrini, Léo Cances:
Cosine-similarity penalty to discriminate sound classes in weakly-supervised sound event detection. IJCNN 2019: 1-8 - [c46]Abdelwahab Heba, Thomas Pellegrini, Jean-Pierre Lorré, Régine André-Obrecht:
Char+CV-CTC: Combining Graphemes and Consonant/Vowel Units for CTC-Based ASR Using Multitask Learning. INTERSPEECH 2019: 1611-1615 - [c45]Thomas Pellegrini, Jérôme Farinas, Estelle Delpech, François Lancelot:
The Airbus Air Traffic Control Speech Recognition 2018 Challenge: Towards ATC Automatic Transcription and Call Sign Detection. INTERSPEECH 2019: 2993-2997 - [c44]Léo Cances, Patrice Guyot, Thomas Pellegrini:
Evaluation of Post-Processing Algorithms for Polyphonic Sound Event Detection. WASPAA 2019: 318-322 - [i5]Thomas Pellegrini, Léo Cances:
Cosine-similarity penalty to discriminate sound classes in weakly-supervised sound event detection. CoRR abs/1901.03146 (2019) - [i4]Léo Cances, Patrice Guyot, Thomas Pellegrini:
Evaluation of post-processing algorithms for polyphonic sound event detection. CoRR abs/1906.06909 (2019) - [i3]Romain Zimmer, Thomas Pellegrini, Srisht Fateh Singh, Timothée Masquelier:
Technical report: supervised training of convolutional spiking neural networks with PyTorch. CoRR abs/1911.10124 (2019) - 2018
- [c43]Léo Cances, Thomas Pellegrini, Patrice Guyot:
Sound event detection from weak annotations: weighted-GRU versus multi-instance-learning. DCASE 2018: 64-68 - [c42]Sarah Cosentino, Estelle I. S. Randria, Jia-Yeu Lin, Thomas Pellegrini, Salvatore Sessa, Atsuo Takanishi:
Group emotion recognition strategies for entertainment robots. IROS 2018: 813-818 - [i2]Thomas Pellegrini:
Densely Connected CNNs for Bird Audio Detection. CoRR abs/1807.02776 (2018) - [i1]Thomas Pellegrini, Jérôme Farinas, Estelle Delpech, François Lancelot:
The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection. CoRR abs/1810.12614 (2018) - 2017
- [c41]Christine Sénac, Thomas Pellegrini, Florian Mouret, Julien Pinquier:
Music Feature Maps with Convolutional Neural Networks for Music Genre Classification. CBMI 2017: 19:1-19:5 - [c40]Thomas Pellegrini:
Densely connected CNNs for bird audio detection. EUSIPCO 2017: 1734-1738 - [c39]Céline Manenti, Thomas Pellegrini, Julien Pinquier:
Unsupervised Speech Unit Discovery Using K-means and Neural Networks. SLSP 2017: 169-180 - [c38]Abdelwahab Heba, Thomas Pellegrini, Tom Jorquera, Régine André-Obrecht, Jean-Pierre Lorré:
Lexical Emphasis Detection in Spoken French Using F-BANKs and Neural Networks. SLSP 2017: 241-249 - 2016
- [c37]Marwa Thlithi, Julien Pinquier, Thomas Pellegrini, Régine André-Obrecht:
Filterbank coefficients selection for segmentation in singer turns. CBMI 2016: 1-6 - [c36]Thomas Pellegrini, Sandrine Mouysset:
Inferring Phonemic Classes from CNN Activation Maps Using Clustering Techniques. INTERSPEECH 2016: 1290-1294 - [c35]Patrice Guyot, Alice Eldridge, Ying Chen Eyre-Walker, Alison Johnston, Thomas Pellegrini, Mika Peck:
Sinusoidal Modelling for Ecoacoustics. INTERSPEECH 2016: 2602-2606 - [c34]Vincent Laborde, Thomas Pellegrini, Lionel Fontan, Julie Mauclair, Halima Sahraoui, Jérôme Farinas:
Pronunciation Assessment of Japanese Learners of French with GOP Scores and Phonetic Information. INTERSPEECH 2016: 2686-2690 - [c33]Céline Manenti, Thomas Pellegrini, Julien Pinquier:
CNN-Based Phone Segmentation Experiments in a Less-Represented Language. INTERSPEECH 2016: 3549-3553 - [c32]Céline Manenti, Thomas Pellegrini, Julien Pinquier:
Influence de la quantité de données sur une tâche de segmentation de phones fondée sur les réseaux de neurones (Phone-level speech segmentation with neural networks : influence of the amount of data ). JEP-TALN-RECITAL (1) 2016: 392-400 - [c31]Thomas Pellegrini, Lionel Fontan, Halima Sahraoui:
Réseau de neurones convolutif pour l'évaluation automatique de la prononciation (CNN-based automatic pronunciation assessment of Japanese speakers learning French ). JEP-TALN-RECITAL (1) 2016: 624-632 - 2015
- [j3]Thomas Pellegrini, Lionel Fontan, Julie Mauclair, Jérôme Farinas, Charlotte Alazard-Guiu, Marina Robert, Peggy Gatignol:
Automatic Assessment of Speech Capability Loss in Disordered Speech. ACM Trans. Access. Comput. 6(3): 8:1-8:14 (2015) - [c30]Vincent Bragard, Thomas Pellegrini, Julien Pinquier:
Pyc2Sound: a Python tool to convert images into sound. Audio Mostly Conference 2015: 7:1-7:4 - [c29]Thomas Pellegrini:
Comparing SVM, softmax, and shallow neural networks for eating condition classification. INTERSPEECH 2015: 899-903 - [c28]Thomas Pellegrini, Valentin Barrière:
Time-continuous Estimation of Emotion in Music with Recurrent Neural Networks. MediaEval 2015 - [c27]Lionel Fontan, Thomas Pellegrini, Julia Olcoz, Alberto Abad:
Predicting disordered speech comprehensibility from Goodness of Pronunciation scores. SLPAT@Interspeech 2015: 42-46 - 2014
- [c26]Thomas Pellegrini, Patrice Guyot, Baptiste Angles, Christophe Mollaret, Christophe Mangou:
Towards soundpainting gesture recognition. Audio Mostly Conference 2014: 18:1-18:6 - [c25]Thomas Pellegrini, Lionel Fontan, Julie Mauclair, Jérôme Farinas, Marina Robert:
The goodness of pronunciation algorithm applied to disordered speech. INTERSPEECH 2014: 1463-1467 - [c24]Marwa Thlithi, Thomas Pellegrini, Julien Pinquier, Régine André-Obrecht:
Segmentation in singer turns with the Bayesian information criterion. INTERSPEECH 2014: 1988-1992 - [c23]Thomas Pellegrini, Vahid Hedayati, Isabel Trancoso, Annika Hämäläinen, Miguel Sales Dias:
Speaker age estimation for elderly speech recognition in European Portuguese. INTERSPEECH 2014: 2962-2966 - [c22]Thomas Pellegrini, Vahid Hedayati, Ângela Costa:
El-WOZ: a client-server wizard-of-oz interface. LREC 2014: 279-282 - [c21]Annika Hämäläinen, Hyongsil Cho, Sara Candeias, Thomas Pellegrini, Alberto Abad, Michael Tjalve, Isabel Trancoso, Miguel Sales Dias:
Automatically Recognising European Portuguese Children's Speech - Pronunciation Patterns Revealed by an Analysis of ASR Errors. PROPOR 2014: 1-11 - [c20]Annika Hämäläinen, Hugo Meinedo, Michael Tjalve, Thomas Pellegrini, Isabel Trancoso, Miguel Sales Dias:
Improving Speech Recognition through Automatic Selection of Age Group - Specific Acoustic Models. PROPOR 2014: 12-23 - [c19]Annika Hämäläinen, Sara Candeias, Hyongsil Cho, Hugo Meinedo, Alberto Abad, Thomas Pellegrini, Michael Tjalve, Isabel Trancoso, Miguel Sales Dias:
Correlating ASR errors with developmental changes in speech production: a study of 3-10-year-old European Portuguese children's speech. WOCCI 2014: 7-13 - 2013
- [j2]Thomas Pellegrini, Rui Correia, Isabel Trancoso, Jorge Baptista, Nuno J. Mamede, Maxine Eskénazi:
ASR-based exercises for listening comprehension practice in European Portuguese. Comput. Speech Lang. 27(5): 1127-1142 (2013) - [c18]Thomas Pellegrini, Annika Hämäläinen, Philippe Boula de Mareüil, Michael Tjalve, Isabel Trancoso, Sara Candeias, Miguel Sales Dias, Daniela Braga:
A corpus-based study of elderly and young speakers of European Portuguese: acoustic correlates and their impact on speech recognition performance. INTERSPEECH 2013: 852-856 - 2012
- [c17]Thomas Pellegrini, Wang Ling, André Silva, Rui Correia, Isabel Trancoso, Jorge Baptista, Nuno J. Mamede:
Overview of Computer-assisted Language Learning for European Portuguese at L2f. CSEDU (2) 2012: 538-543 - [c16]Thomas Pellegrini, Isabel Trancoso, Annika Hämäläinen, António Calado, Miguel Sales Dias, Daniela Braga:
Impact of Age in ASR for the Elderly: Preliminary Experiments in European Portuguese. IberSPEECH 2012: 139-147 - [c15]Thomas Pellegrini, Ângela Costa, Isabel Trancoso:
Less errors with TTS? A dictation experiment with foreign language learners. INTERSPEECH 2012: 1291-1294 - 2011
- [c14]Virginia Barbosa, Thomas Pellegrini, Miguel M. F. Bugalho, Isabel Trancoso:
Browsing videos by automatically detected audio events. EUROCON 2011: 1-4 - [c13]Thomas Pellegrini, Rui Correia, Isabel Trancoso, Jorge Baptista, Nuno J. Mamede:
Automatic Generation of Listening Comprehension Learning Material in European Portuguese. INTERSPEECH 2011: 1629-1632 - [c12]Rui Correia, Thomas Pellegrini, Maxine Eskénazi, Isabel Trancoso, Jorge Baptista, Nuno J. Mamede:
Listening comprehension games for portuguese: exploring the best features. SLaTE 2011: 5-8 - 2010
- [c11]Thomas Pellegrini, Isabel Trancoso:
Improving ASR error detection with non-decoder based features. INTERSPEECH 2010: 1950-1953 - [c10]Alberto Abad, Thomas Pellegrini, Isabel Trancoso, João Paulo Neto:
Context dependent modelling approaches for hybrid speech recognizers. INTERSPEECH 2010: 2950-2953 - [c9]José Lopes, Isabel Trancoso, Rui Correia, Thomas Pellegrini, Hugo Meinedo, Nuno J. Mamede, Maxine Eskénazi:
Multimedia learning materials. SLT 2010: 121-126
2000 – 2009
- 2009
- [j1]Thomas Pellegrini, Lori Lamel:
Automatic Word Decompounding for ASR in a Morphologically Rich Language: Application to Amharic. IEEE Trans. Speech Audio Process. 17(5): 863-873 (2009) - [c8]Isabel Trancoso, Thomas Pellegrini, José Portelo, Hugo Meinedo, Miguel M. F. Bugalho, Alberto Abad, João Paulo Neto:
Audio contributions to semantic video search. ICME 2009: 630-633 - [c7]Miguel M. F. Bugalho, José Portelo, Isabel Trancoso, Thomas Pellegrini, Alberto Abad:
Detecting audio events for semantic video search. INTERSPEECH 2009: 1151-1154 - [c6]Thomas Pellegrini, Isabel Trancoso:
Error Detection in Broadcast News ASR Using Markov Chains. LTC 2009: 59-69 - 2008
- [b1]Thomas Pellegrini:
Transcription automatique de langues peu dotées. (Automatic speech recognition for less-represented languages). University of Paris-Sud, Orsay, France, 2008 - [c5]Martine Adda-Decker, Thomas Pellegrini, Éric Bilinski, Gilles Adda:
Developments of "Lëtzebuergesch" Resources for Automatic Speech Processing and Linguistic Studies. LREC 2008 - [c4]Thomas Pellegrini, Lori Lamel:
Are audio or textual training data more important for ASR in less-represented languages? SLTU 2008: 2-6 - 2007
- [c3]Thomas Pellegrini, Lori Lamel:
Using phonetic features in unsupervised word decompounding for ASR with application to a less-represented language. INTERSPEECH 2007: 1797-1800 - 2006
- [c2]Thomas Pellegrini, Lori Lamel:
Investigating automatic decomposition for ASR in less represented languages. INTERSPEECH 2006 - [c1]Thomas Pellegrini, Lori Lamel:
Experimental detection of vowel pronunciation variants in Amharic. LREC 2006: 1005-1008
Coauthor Index
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