Date	Type	Author	Title	Journal	Link
-	-	-	as Télécom Paris (see IRCAM web page for others)	-	-
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	-
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	-
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