most citedPreserving the beamforming effect for spatial cue-based pseudo-binaural dereverberation of a single source

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SD2024

Exploiting Consistency-Preserving Loss and Perceptual Contrast Stretching to Boost SSL-based Speech Enhancement

Muhammad Salman Khan, Moreno La Quatra, Kuo-Hsuan Hung +3

Self-supervised representation learning (SSL) has attained SOTA results on several downstream speech tasks, but SSL-based speech enhancement (SE) solutions still lag behind. To add…

eess.AS20233 cited

Single channel speech enhancement by colored spectrograms

Sania Gul, Muhammad Salman Khan, Muhammad Fazeel

Speech enhancement concerns the processes required to remove unwanted background sounds from the target speech to improve its quality and intelligibility. In this paper, a novel ap…

cs.SD2023

Blind Restoration of Real-World Audio by 1D Operational GANs

Turker Ince, Serkan Kiranyaz, Ozer Can Devecioglu +3

Objective: Despite numerous studies proposed for audio restoration in the literature, most of them focus on an isolated restoration problem such as denoising or dereverberation, ig…

eess.AS20221 cited

Preserving the beamforming effect for spatial cue-based pseudo-binaural dereverberation of a single source

Sania Gul, Muhammad Salman Khan, Syed Waqar Shah

Reverberations are unavoidable in enclosures, resulting in reduced intelligibility for hearing impaired and non native listeners and even for the normal hearing listeners in noisy…

eess.AS20221 cited

Recycling an anechoic pre-trained speech separation deep neural network for binaural dereverberation of a single source

Sania Gul, Muhammad Salman Khan, Syed Waqar Shah +1

Reverberation results in reduced intelligibility for both normal and hearing-impaired listeners. This paper presents a novel psychoacoustic approach of dereverberation of a single…