Lyrics-based analysis and classification of music M Fell, C Sporleder Proceedings of COLING 2014, the 25th international conference on …, 2014 | 64 | 2014 |
An ensemble approach of recurrent neural networks using pre-trained embeddings for playlist completion D Monti, E Palumbo, G Rizzo, P Lisena, R Troncy, M Fell, E Cabrio, ... Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018 | 10 | 2018 |
Lyrics classification M Fell Master's Thesis: Saarland University, 2014 | 9 | 2014 |
Lyrics segmentation: Textual macrostructure detection using convolutions M Fell, Y Nechaev, E Cabrio, F Gandon | 8 | 2018 |
Song lyrics summarization inspired by audio thumbnailing M Fell, E Cabrio, F Gandon, A Giboin | 7 | 2019 |
Comparing Automated Methods to Detect Explicit Content in Song Lyrics M Fell, E Cabrio, M Corazza, F Gandon Proceedings of the International Conference on Recent Advances in Natural …, 2019 | 4 | 2019 |
Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations M Fell, E Cabrio, E Korfed, M Buffa, F Gandon arXiv preprint arXiv:1912.02477, 2019 | 3 | 2019 |
Verbal irony: Theories and automatic detection M Fell GRIN Verlag, 2012 | 3 | 2012 |
The WASABI dataset: cultural, lyrics and audio analysis metadata about 2 million popular commercially released songs M Buffa, E Cabrio, FL Gandon, M Fell, A Giboin, F Michel, M Tikat, ... | | 2020 |
Natural Language Processing for Music Information Retrieval: Deep Analysis of Lyrics Structure and Content M Fell Université Côte D’Azur, 2020 | | 2020 |