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Found 5 papers, 0 papers with code
MC-SEMamba: A Simple Multi-channel Extension of SEMamba
In particular, models like SEMamba have demonstrated the effectiveness of the Mamba architecture in single-channel speech enhancement.
Robust Audio-Visual Speech Enhancement: Correcting Misassignments in Complex Environments with Advanced Post-Processing
This paper addresses the prevalent issue of incorrect speech output in audio-visual speech enhancement (AVSE) systems, which is often caused by poor video quality and mismatched training and test data.
Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement
In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction.
EMO-Codec: An In-Depth Look at Emotion Preservation capacity of Legacy and Neural Codec Models With Subjective and Objective Evaluations
The neural codec model reduces speech data transmission delay and serves as the foundational tokenizer for speech language models (speech LMs).
Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement
Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems.
