From the 1 of 6 linked papers with an AI index.
6 papers
Spacing Out: On the Reliability of Binaural Music Source Separation Metrics
Richa Namballa, Magdalena Fuentes
The paper investigates how well objective spatial distortion metrics reflect human perception in binaural music source separation, revealing inconsistencies and evaluating alternat…
Investigating Modality Contribution in Audio LLMs for Music
Giovana Morais, Magdalena Fuentes
Audio Large Language Models (Audio LLMs) enable human-like conversation about music, yet it is unclear if they are truly listening to the audio or just using textual reasoning, as…
Live Vocal Extraction from K-pop Performances
Yujin Kim, Richa Namballa, Magdalena Fuentes
K-pop's global success is fueled by its dynamic performances and vibrant fan engagement. Inspired by K-pop fan culture, we propose a methodology for automatically extracting live v…
Do Music Source Separation Models Preserve Spatial Information in Binaural Audio?
Richa Namballa, Agnieszka Roginska, Magdalena Fuentes
Binaural audio remains underexplored within the music information retrieval community. Motivated by the rising popularity of virtual and augmented reality experiences as well as po…
Musical Source Separation of Brazilian Percussion
Richa Namballa, Giovana Morais, Magdalena Fuentes
Musical source separation (MSS) has recently seen a big breakthrough in separating instruments from a mixture in the context of Western music, but research on non-Western instrumen…
Skip That Beat: Augmenting Meter Tracking Models for Underrepresented Time Signatures
Giovana Morais, Brian McFee, Magdalena Fuentes
Beat and downbeat tracking models are predominantly developed using datasets with music in 4/4 meter, which decreases their generalization to repertories in other time signatures,…