32 citations · 45 across the 9 of their papers we have counts for
9 papers
Subspace Hybrid Beamforming for Head-worn Microphone Arrays
Sina Hafezi, Alastair H. Moore, Pierre Guiraud +4
A two-stage multi-channel speech enhancement method is proposed which consists of a novel adaptive beamformer, Hybrid Minimum Variance Distortionless Response (MVDR), Isotropic-MVD…
ReVISE: Self-Supervised Speech Resynthesis with Visual Input for Universal and Generalized Speech Enhancement
Wei-Ning Hsu, Tal Remez, Bowen Shi +2
Prior works on improving speech quality with visual input typically study each type of auditory distortion separately (e.g., separation, inpainting, video-to-speech) and present ta…
LA-VocE: Low-SNR Audio-visual Speech Enhancement using Neural Vocoders
Rodrigo Mira, Buye Xu, Jacob Donley +4
Audio-visual speech enhancement aims to extract clean speech from a noisy environment by leveraging not only the audio itself but also the target speaker's lip movements. This appr…
The impact of removing head movements on audio-visual speech enhancement
Zhiqi Kang, Mostafa Sadeghi, Radu Horaud +3
This paper investigates the impact of head movements on audio-visual speech enhancement (AVSE). Although being a common conversational feature, head movements have been ignored by…
NICE-Beam: Neural Integrated Covariance Estimators for Time-Varying Beamformers
Jonah Casebeer, Jacob Donley, Daniel Wong +2
Estimating a time-varying spatial covariance matrix for a beamforming algorithm is a challenging task, especially for wearable devices, as the algorithm must compensate for time-va…
Multichannel Speech Enhancement without Beamforming
Asutosh Pandey, Buye Xu, Anurag Kumar +3
Deep neural networks are often coupled with traditional spatial filters, such as MVDR beamformers for effectively exploiting spatial information. Even though single-stage end-to-en…
Time-domain Ad-hoc Array Speech Enhancement Using a Triple-path Network
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
Deep neural networks (DNNs) are very effective for multichannel speech enhancement with fixed array geometries. However, it is not trivial to use DNNs for ad-hoc arrays with unknow…
TPARN: Triple-path Attentive Recurrent Network for Time-domain Multichannel Speech Enhancement
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
In this work, we propose a new model called triple-path attentive recurrent network (TPARN) for multichannel speech enhancement in the time domain. TPARN extends a single-channel d…
EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments
Jacob Donley, Vladimir Tourbabin, Jung-Suk Lee +6
Augmented Reality (AR) as a platform has the potential to facilitate the reduction of the cocktail party effect. Future AR headsets could potentially leverage information from an a…