3 papers
eess.AS2026
Mind the Gap: Detecting Cluster Exits for Robust Local Density-Based Score Normalization in Anomalous Sound Detection
Kevin Wilkinghoff, Gordon Wichern, Jonathan Le Roux +1
Local density-based score normalization is an effective component of distance-based embedding methods for anomalous sound detection, particularly when data densities vary across co…
cs.SD2025
FasTUSS: Faster Task-Aware Unified Source Separation
Francesco Paissan, Gordon Wichern, Yoshiki Masuyama +4
Time-Frequency (TF) dual-path models are currently among the best performing audio source separation network architectures, achieving state-of-the-art performance in speech enhance…
eess.AS2024
Task-Aware Unified Source Separation
Kohei Saijo, Janek Ebbers, François G. Germain +2
Several attempts have been made to handle multiple source separation tasks such as speech enhancement, speech separation, sound event separation, music source separation (MSS), or…