We have published 12 theses that have been carried out and finished during the academic year 2021-2022 in the Master in Sound and Music Computing. Here is the list of the theses:

• Anna Eliane Barletta: Generating Classical Music Playlists using Radio Broadcast Programming
• Betty Cortiñas Lorenzo: Transcription-Guided and Self-Supervised Speech Representations for Singing Voice Conversion
• Christos Filippidis: Singing Voice Separation Using Interpretable Deep Learning
• Dean Cochran: Heterogeneous Graph Neural Network Music Recommendation
• Gustav Anthon: Evaluation of Nonlinearities in a Diode Clipper Circuit based on Wave Digital Filters
• Huicheng Zhang: Hierarchical Music Source Separation Using Mixing Secret Multi-track Dataset
• Lennart Nicolas Krebs: A Comparative Study On Improving Sound Similarity Maps With Semantic Metadata
• Marco Bertola: Exploring Data Augmentation Techniques for Sound Event Detection
• Miquel Royo: Evaluation of Tube Screamer Simulation using Machine Learning
• Rajsuryan Singh: Multimodal Urban Scene Understanding
• Samuel Narváez: Advancing a Wavelet-Based Spatial Audio Format
• Sultan Eylem Atabay: Desktop Interface for Freesound-based Sampler Audio Plugin

Master thesis from previous years are also accessible here: https://zenodo.org/communities/smc-master