Location as Supervision for Weakly Supervised Multi-Channel Source Separation of Machine Sounds
Author:
Affiliation:
1. Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10248019/10248047/10248128.pdf?arnumber=10248128
Reference38 articles.
1. Listen to What You Want: Neural Network-Based Universal Sound Selector
2. Conditioned Source Separation for Musical Instrument Performances
3. Improving Universal Sound Separation Using Sound Classification
4. A two-stage U-net for high-fidelity de-noising of historical recordings;moliner;Proc ICASSP,2022
5. Finding Strength in Weakness: Learning to Separate Sounds with Weak Supervision
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1. Acoustic-Scene-Aware Target Sound Separation With Sound Embedding Refinement;IEEE Access;2024
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