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Cross-Domain Retrieval in the Legal and Patent Domains: A Reproducibility Study Read chapter Read first chapter

2021 | OriginalPaper | Chapter

LEMONS: Listenable Explanations for Music recOmmeNder Systems

Authors : Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer

Published in: Advances in Information Retrieval

Publisher: Springer International Publishing

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Abstract

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.

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Footnotes
2
Details about training and architecture can be found in our GitHub repository.
 
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Metadata
Title
LEMONS: Listenable Explanations for Music recOmmeNder Systems
Authors
Alessandro B. Melchiorre
Verena Haunschmid
Markus Schedl
Gerhard Widmer
Copyright Year
2021
Book
Advances in Information Retrieval

Print ISBN: 978-3-030-72239-5

Electronic ISBN: 978-3-030-72240-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-72240-1_60