Analysis and interpretation of joint source separation and sound event detection in domestic environments

journal article in Web of Science

English

In recent years, the relation between Sound Event Detection (SED) and Source Separation (SSep) has received a growing interest, in particular, with the aim to enhance the performance of SED by leveraging the synergies between both tasks. In this paper, we present a detailed description of JSS (Joint Source Separation and Sound Event Detection), our joint-training scheme for SSep and SED, and we measure its performance in the DCASE Challenge for SED in domestic environments. Our experiments demonstrate that JSS can improve SED performance, in terms of Polyphonic Sound Detection Score (PSDS), even without additional training data. Additionally, we conduct a thorough analysis of JSS's effectiveness across different event classes and in scenarios with severe event overlap, where it is expected to yield further improvements. Furthermore, we introduce an objective measure to assess the diversity of event predictions across the estimated sources, shedding light on how different training strategies impact the separation of sound events. Finally, we provide graphical examples of the Source Separation and Sound Event Detection steps, aiming to facilitate the interpretation of the JSS methods.

article; diagnosis; human; prediction; sound; sound detection; algorithm

DE BENITO GORRON, D.; ŽMOLÍKOVÁ, K.; TORRE TOLEDANO, D.

5. 7. 2024

PUBLIC LIBRARY SCIENCE

SAN FRANCISCO

1932-6203

PLOS ONE

19

7

United States of America

1

30

30

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0303994

http://hdl.handle.net/11012/252544