Multi-Channel Speech Enhancement Using Labelled Random Finite Sets and a Neural Beamformer in Cocktail Party Scenario

Multi-Channel Speech Enhancement Using Labelled Random Finite Sets and a Neural Beamformer in Cocktail Party Scenario

In this research, a multi-channel target speech enhancement scheme is proposed that is based on deep learning (DL) architecture and assisted by multi-source tracking using a labeled random finite set (RFS) framework. A neural network based on minimum variance distortionless response (MVDR) beamforme...

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Bibliographic Details
Main Authors: Jayanta Datta, Ali Dehghan Firoozabadi, David Zabala-Blanco, Francisco R. Castillo-Soria
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
SRP-PHAT
deep learning
microphone array
MS-GLMB filtering
beamforming
Online Access:https://www.mdpi.com/2076-3417/15/6/2944
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