182 citations · 435 across the 38 of their papers we have counts for
12 papers · 1 filter
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…
NORESQA: A Framework for Speech Quality Assessment using Non-Matching References
Pranay Manocha, Buye Xu, Anurag Kumar
The perceptual task of speech quality assessment (SQA) is a challenging task for machines to do. Objective SQA methods that rely on the availability of the corresponding clean refe…
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…
Continual self-training with bootstrapped remixing for speech enhancement
Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu +2
We propose RemixIT, a simple and novel self-supervised training method for speech enhancement. The proposed method is based on a continuously self-training scheme that overcomes li…