LEMONS: Listenable Explanations for Music recOmmeNder Systems



Although current music recommender systems suggest new tracks to their users, they do not provide listenable explanations of why a user should listen to them. LEMONS (Demonstration video: https://youtu.be/giSPrPnZ7mc) is a new system that addresses this gap by (1) adopting a deep learning approach to generate audio content-based recommendations from the audio tracks and (2) providing listenable explanations based on the time-source segmentation of the recommended tracks using the recently proposed audioLIME.


Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer
LEMONS: Listenable Explanations for Music recOmmeNder Systems
European Conference on Information Retrieval, 58(5): 531--536, doi:10.1007/978-3-030-72240-1_60, 2021.


    title = {LEMONS: Listenable Explanations for Music recOmmeNder Systems},
    author = {Melchiorre, Alessandro B. and Haunschmid, Verena and Schedl, Markus and Widmer, Gerhard},
    booktitle = {European Conference on Information Retrieval},
    editor = {Hiemstra, Djoerd and Moens, Marie-Francine and Mothe, Josiane and Perego, Raffaele and Potthast, Martin and Sebastiani, Fabrizio},
    publisher = {Springer International Publishing},
    doi = {10.1007/978-3-030-72240-1_60},
    volume = {58},
    number = {5},
    pages = {531--536},
    year = {2021}