UPF1 “Facilitating Interactive Music Exploration Sample Clauses

UPF1 “Facilitating Interactive Music Exploration. The goal of this project is to improve the music exploration process by replacing typically used discretized tags with a continuous semantic space learned by deep-learning autotaggers and utilizing reinforcement learning and interactivity to optimize the process individually for each user. Regarding the current state of the art on this particular aspect, typical categories of tags that are used for exploration are genres and moods. In the new proposed open autotagging dataset [1] there are 3 defined categories: genre, mood/theme, and instruments. Moods and genres have been used before for exploration [2, 3], but not in conjunction. The biggest challenge in this research is to understand the semantics of the continuous space that is learned by deep-learning autotaggers. Explainability of deep-learning systems is a field of research on its own, thus there are limited resources that can be spent on it in the context of this research.
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UPF1 “Facilitating Interactive Music Exploration. The goal of this project is to improve the music exploration process by replacing typically used discrete tags with a continuous semantic space learned by deep-learning autotaggers and utilizing reinforcement learning and interactivity to optimize the process individually for each user. State of the Art. Recommendation systems normally utilize either collaborative filtering [1] or a content-based approach [2], or mixture of both. State of the art deep-learning autotagger systems [3] commonly use xxx-spectrograms as input, several layers of convolutional neural networks (CNNs) and dense layers (one or more) before the output [4]. There are several open datasets for autotagging [5, 6, 7], however, due to quality and standardization issues, we have proposed a new MTG-Jamendo dataset [8]. Challenges and Opportunities. Nowadays there are multiple autotagging datasets, however, it is difficult to share audio that is copyrighted. Thus, we have proposed a new dataset in collaboration with Jamendo that contains audio that is licensed by creative commons. With the audio openly available and the annotation quality curated by Xxxxxxx, it presents new opportunities for researchers in autotagging and deep-learning.
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UPF1 “Facilitating Interactive Music Exploration 
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