10 papers
SlimDiffuSE: Towards Efficient Diffusion-Based Speech Enhancement using Slimmable Networks
Nagashree K. S. Rao, Shrishti Saha Shetu, Mohamed Elminshawi +2
Diffusion-based models are emerging in the speech enhancement domain and are achieving state-of-the-art performance across various benchmark datasets. A major downside of diffusion…
μNet: Ultra-Low-Memory and Low-Complexity Speech Enhancement for Embedded Digital Signal Processors
Shrishti Saha Shetu, Jose Miguel Martinez Aponte, Nagashree K. S. Rao +3
Speech enhancement on embedded digital signal processors (DSPs) imposes strict constraints on memory footprint, computational complexity, latency, and support for integer operation…
A Comparison of Generative and Discriminative Methods for Speech Enhancement: Robustness, Complexity, and Hallucination
Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel
In this study, we conduct a comprehensive comparative analysis of generative and discriminative deep learning-based speech enhancement methods, specifically in noise reduction task…
GAN-Based Multi-Microphone Spatial Target Speaker Extraction
Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel
Spatial target speaker extraction isolates a desired speaker's voice in multi-speaker environments using spatial information, such as the direction of arrival (DoA). Although recen…
Leveraging Discriminative Latent Representations for Conditioning GAN-Based Speech Enhancement
Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel
Generative speech enhancement methods based on generative adversarial networks (GANs) and diffusion models have shown promising results in various speech enhancement tasks. However…
Align-ULCNet: Towards Low-Complexity and Robust Acoustic Echo and Noise Reduction
Shrishti Saha Shetu, Naveen Kumar Desiraju, Wolfgang Mack +1
The successful deployment of deep learning-based acoustic echo and noise reduction (AENR) methods in consumer devices has spurred interest in developing low-complexity solutions, w…