Geoffroy Peeters

Full professor ◼ Télécom Paris/ IP-Paris ◼ LTCI ◼ Image Data Signal department

Publications


Date Type Author Title Journal Link
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2024 Conference R. Mignot, G. Peeters Invariant Audio Prints for Music Indexing and Alignment In CBMI, Reykjavik, Iceland Link
2024 Conference S. Nabi, Ph. Esling, G. Peeters, F. Bevilacqua Embodied exploration of deep latent spaces in interactive dance-music performance In 9th International Conference on Movement and Computing, Utrecht, the Netherlands Link
2024 Conference A. Riou, St. Lattner, G. Hadjeres, G. Peeters Investigating Design Choices in JEPA for General Audio Representation Learning In IEEE ICASSP, SASB workshop, Seoul, Korea Link
2024 Conference B. Torres, G. Peeters, G. Richard Unsupervised harmonic parameter estimation using differentiable dsp and spectral optimal transport In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Seoul, Korea Link
2024 Conference C. Peladeau, G. Peeters Blind estimation of audio effects using an auto-encoder approach and differentiable digital signal processing In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Seoul, Korea Link
2024 Conference A. Quelennec, M. Olvera, G. Peeters, S. Essid On the choice of the optimal temporal support for audio classification with pre-trained embeddings In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Seoul, Korea Link
2024 Conference A. Gagneré, S. Essid, G. Peeters Adapting pitch-based self supervised learning models for tempo estimation In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Seoul, Korea Link
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2023 Conference G. Peeters Self-Similarity-Based and Novelty-based loss for music structure analysis In Proc. of ISMIR (International Society for Music Information Retrieval), Milano, Italy Link
2023 Conference A. Riou, St. Lattner, G. Hadjeres, G. Peeters PESTO: Pitch Estimation with Self-supervised Transposition-equivariant Objective In Proc. of ISMIR (International Society for Music Information Retrieval), Milano, Italy Link
2023 Conference F. Mathieu, T. Courtat, G. Richard, and G. Peeters Learning interpretable filters in wav-unet for speech enhancement In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Rhodes, Greece Link
2023 Conference F. Angulo, S. Essid, G. Peeters, and C. Mietlicki Cosmopolite sound monitoring (cosmo) : A study of urban sound event detection systems generalizing to multiple cities In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Rhodes, Greece Link
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2022 Conference/ LBD G. Peeters and F. Angulo Ssm-net: Feature learning for music structure analysis using differentiable self-similarity-matrix In Proc. of ISMIR (International Society for Music Information Retrieval), Bengaluru, India Link
2022 Conference K. M. Ibrahim, E. V. Epure, G. Peeters, and G. Richard Exploiting device and audio data to tag music with user-aware listening contexts In Proc. of ISMIR (International Society for Music Information Retrieval), Bengaluru, India Link
2022 Conference F. Mathieu, T. Courtat, G. Richard, and G. Peeters Phase shifted bedrosian filterbank: An interpretable audio front-end for time-domain audio source separatio In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Singapore, Singapore Link
2022 Journal P. Proutskova, D. Wolff, G. Fazekas, K. Frieler, F. Ho ̈ger, O. Velichkina, G. Solis, T. Weyde, M. Pfleiderer, H.-C. Crayencour, G. Peeters, and S. Dixon The jazz ontology: A semantic model and large-scale rdf repositories for jazz Journal of Web Semantics Link
2022 Journal C. Weiß and G. Peeters Comparing deep models and evaluation strategies for multi-pitch estimation in music recordings IEEE Transactions on Audio, Speech and Language Processing Link
2022 Journal L. Pretet, G. Richard, C. Souchier, and G. Peeters Video-to-music recommendation using temporal alignment of segments IEEE Transactions on Multimedia Link
2022 Journal H. Foroughmand and G. Peeters. Extending Deep Rhythm for Tempo and Genre Estimation Using Complex Convolutions, Multitask Learning and Multi-input Network Journal of Creative Music System Link
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2021 Journal M. Fell, Y. Nechaev, G. Meseguer-Brocal, E. Cabrio, F. Gando, and G. Peeters Lyrics segmentation via bimodal text-audio representation Natural Language Engineering Link
2021 Conference C. Weiß and G. Peeters Learning multi-pitch estimation from weakly aligned score–audio pairs using a multi-label CTC loss In Proc. of IEEE WASPAA (Workshop on Applications of Signal Processing to Audio and Acoustics), New Paltz, NY, USA Link
2021 Conference L. Pretet, G. Richard, and G. Peeters Music-video recommendation cross-modal music-video recommen- dation: A study of design choice In Proc. of IJCNN (International Joint Conference on Neural Networks), Virtual Event (Shenzhen, China) Link
2021 Conference C. Weiß and G. Peeters Training deep pitch-class representations with a multi-label CTC loss In Proc. of ISMIR (International Society for Music Information Retrieval), Online Link
2021 Conference L. Pretet, G. Richard, and G. Peeters Is there a “language of music-video clips” ? a qualitative and quantitative study In Proc. of ISMIR (International Society for Music Information Retrieval), Online Link
2021 Book chapter G. Peeters The deep learning revolution in mir: the pros and cons, the needs and the challenges In LNCS 12631 - Perception, Representations, Image, Sound, Music. CMMR 2019, Lecture Notes in Computer Science. Springer-Verlag Link
2021 Book chapter G. Peeters and G. Richard Deep learning for audio and music In J. Benois-Pineau and Z. Akka, editors, Multi-faceted Deep Learning: Models and Data, chapter 11. Springer Verlag Link
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2020 Conference G. Meseguer Brocal and G. Peeters Content based singing voice source separation via strong conditioning using aligned phonemes In Proc. of ISMIR (International Society for Music Information Retrieval), Montreal, Canada Link
2020 Conference K. M. Ibrahim, E. V. Epure, G. Peeters, and G. Richard *Should we consider the users in contextual music auto-tagging models? * In Proc. of ISMIR (International Society for Music Information Retrieval), Montreal, Canada Link
2020 Conference G. Doras, F. Yesiler, J. Serra, E. Gomez, and G. Peeters Combining musical features for cover detection In Proc. of ISMIR (International Society for Music Information Retrieval), Montreal, Canada Link
2020 Conference H. Foroughmand and G. Peeters. Extending deep rhythm for tempo and genre estimation using complex convolutions, multitask learning and multi-input network In Proc. of Joint Conference on AI Music Creativity, Royal Institute of Technology (KTH), Stockholm, Sweden Link
2020 Conference K. M. Ibrahim, E. V. Epure, G. Peeters, and G. Richard Confidence-based weighted loss for multi- label classification with missing labels In ACM International Conference on Multimedia Retrieval 2020 (ICMR 2020), Dublin, Ireland Link
2020 Conference L. Pretet, G. Richard, and G. Peeters Learning to rank music tracks using triplet loss In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Barcelona, Spain Link
2020 Conference G. Doras and G. Peeters A prototypical triplet loss for cover detection In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Barcelona, Spain Link
2020 Conference K. M. Ibrahim, J. Royo-Letelier, E. Epure, G. Peeters, and G. Richard Audio-based auto-tagging with contextual tags for music In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Barcelona, Spain Link
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2019 Journal R. Mignot and G. Peeters An analysis of the effect of data augmentation methods: Experiments for a musical genre classification task Transactions of the International Society for Music Information Retrieval, 2(1):97–110 Link
2019 Conference K. Frieler, D. Basaran, F. Hoger, H.-C. Crayencour, G. Peeters, and S. Dixon. Don’t hide in the frames: Note- and pattern-based evaluation of automated melody extraction algorithms In Proc. of DLfM (International Conference on Digital Libraries for Musicology), The Hague, The Netherlands Link
2019 Conference G. Doras and G. Peeters Cover detection using dominant melody embeddings In Proc. of ISMIR (International Society for Music Information Retrieval), Delft, The Netherlands Link
2019 Conference H. Foroughmand and G. Peeters Deep-rhythm for global tempo estimation in music In Proc. of ISMIR (International Society for Music Information Retrieval), Delft, The Netherlands Link
2019 Conference G. Meseguer Brocal and G. Peeters Conditioned-u-net: Introducing a control mechanism in the u-net for multiple source separations In Proc. of ISMIR (International Society for Music Information Retrieval), Delft, The Netherlands Link
2019 Conference A. Cohen-Hadria, A. Roebel, and G. Peeters Improving singing voice separation using deep u-net and wave-u-net with data augmentation In Proc. of EUSIPCO (European Signal Processing Conference), Coruña, Spain Link
2019 Conference G. Doras, P. Esling, and G. Peeters On the use of u-net for dominant melody estimation in polyphonic music In Proc. of First International Workshop on Multilayer Music Representation and Processing (MMRP19), Milan, Italy Link
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2018 Conference D. Basaran, S. Essid, and G. Peeters Main melody extraction with source-filter nmf and c-rnn. In Proc. of ISMIR (International Society for Music Information Retrieval), Paris, France Link
2018 Conference G. Meseguer Brocal, A. Cohen-Hadria, and G. Peeters Dali: A large dataset of synchronized audio, lyrics and pitch, automatically created using teacher-student In Proc. of ISMIR (International Society for Music Information Retrieval), Paris, France Link
2018 Conference H. Foroughmand and G. Peeters Music retiler: Using nmf2d source separation for audio mosaicing In Audio Mostly (a conference on intercation with sound), Wrexham Glyndwr University (North Wales, UK) Link
2018 Journal D. Fourer, F. Auger, and G. Peeters. Local am/fm parameters estimation: application to sinusoidal modeling and blind audio source separation IEEE Signal Processing Letters, 25(10):1600 – 1604 Link
2018 Conference D. Fourer and G. Peeters Fast and adaptive blind audio source separation using recursive levenberg- marquardt synchrosqueezing In Proc. of IEEE ICASSP (International Conference on Acoustics, Speech, and Signal Processing), Calgary, Alberta, Canada Link