7 citations · 8 across the 9 of their papers we have counts for
5 papers · 1 filter
Mixture-of-Experts Framework for Field-of-View Enhanced Signal-Dependent Binauralization of Moving Talkers
Manan Mittal, Thomas Deppisch, Joseph Forrer +4
We propose a novel mixture of experts framework for field-of-view enhancement in binaural signal matching. Our approach enables dynamic spatial audio rendering that adapts to conti…
All Neural Low-latency Directional Speech Extraction
Ashutosh Pandey, Sanha Lee, Juan Azcarreta +2
We introduce a novel all neural model for low-latency directional speech extraction. The model uses direction of arrival (DOA) embeddings from a predefined spatial grid, which are…
On the Importance of Neural Wiener Filter for Resource Efficient Multichannel Speech Enhancement
Tsun-An Hsieh, Jacob Donley, Daniel Wong +2
We introduce a time-domain framework for efficient multichannel speech enhancement, emphasizing low latency and computational efficiency. This framework incorporates two compact de…
Rethinking complex-valued deep neural networks for monaural speech enhancement
Haibin Wu, Ke Tan, Buye Xu +2
Despite multiple efforts made towards adopting complex-valued deep neural networks (DNNs), it remains an open question whether complex-valued DNNs are generally more effective than…
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…