3 papers
cs.SD2026
Teaching Speech Enhancement Models to Sing: Domain Adaptation from Speech Enhancement to Singing Voice Separation
Paul A. Bereuter, Mark D. Plumbley, Alois Sontacchi
State-of-the-art speech enhancement models benefit from large-scale labeled datasets, whereas singing voice separation models suffer from limited available training data. To addres…
eess.AS2026
Embedding-Based Intrusive Evaluation Metrics for Musical Source Separation Using MERT Representations
Paul A. Bereuter, Alois Sontacchi
Evaluation of musical source separation (MSS) has traditionally relied on Blind Source Separation Evaluation (BSS-Eval) metrics. However, recent work suggests that BSS-Eval metrics…
eess.AS2025
Towards Reliable Objective Evaluation Metrics for Generative Singing Voice Separation Models
Paul A. Bereuter, Benjamin Stahl, Mark D. Plumbley +1
Traditional Blind Source Separation Evaluation (BSS-Eval) metrics were originally designed to evaluate linear audio source separation models based on methods such as time-frequency…