Workplan

WP1: User modeling and personalization

This WP aims at building the user modeling and personalization module, through (a) well-designed questionnaires regarding the possible alteration of the user’s musical preferences during COVID-19 and (b) the extraction of features from users’ listening history, which will be correlated with the results of (a).

Task 1.1 User Recruitment

Task 1.2 Sentiment shift analysis

Task 1.3 Feature Extraction and Analysis from User Playlists

WP2: Core Music Information Retrieval Technologies

The objectives of WP2 are to: i) Explore feature representations for all the core modules – music emotion recognition, music similarity and music source separation – included in the music recommendation system. ii) Build machine and deep learning models for the various modules. 

Task2.1 Literature review and data specification

Task 2.2 Music emotion recognition

Task 2.3 Music source separation

Task 2.4 Music signal processing for music similarity

WP3: Smart personalized music recommendation system

The objectives of this WP3 are to: i) develop the final smart personalized music recommendation and playlist generation system, ii) validate the developed algorithms through perceptual user tests and iii) employ results of the sentiment shift analysis for refinement and retraining of the developed models. 

Task 3.1 Perceptual user tests

Task 3.2 Music Recommendation

WP4: Project Management, Dissemination and Exploitation

Task 4.1 Management and Administration

Task 4.2 Dissemination & Exploitation