Results 71 to 80 of about 2,995 (171)

ICASSP 2023 Deep Noise Suppression Challenge

IEEE Open Journal of Signal Processing
The ICASSP 2023 Deep Noise Suppression (DNS) Challenge marks the fifth edition of the DNS challenge series. DNS challenges were organized from 2019 to 2023 to foster research in the field of DNS.
Harishchandra Dubey, Ashkan Aazami, Vishak Gopal, Babak Naderi, Sebastian Braun, Ross Cutler, Alex Ju, Mehdi Zohourian, Min Tang, Mehrsa Golestaneh, Robert Aichner   +10 more
doaj   +1 more source

Speech dereverberation

, 2005
The effect of reverberation on speech is to cause it to sound distant and spectrally distorted and can also reduce intelligibility. Dereverberation is therefore an important speech enhancement process for hands-free terminals. This is a blind problem and currently an unsolved problem. This paper reviews existing ap- proaches and discuss current work on
Naylor, P, Gaubitch, N
openaire   +1 more source

Effect of Reverberation on Neural Responses to Natural Speech in Rabbit Auditory Midbrain: No Evidence for a Neural Dereverberation Mechanism. [PDF]

eNeuro, 2023
Barzelay O, David S, Delgutte B.
europepmc   +1 more source

FlexLip: A Controllable Text-to-Lip System. [PDF]

Sensors (Basel), 2022
Oneață D, Lőrincz B, Stan A, Cucu H.
europepmc   +1 more source

Iteratively Refined Multi-Channel Speech Separation

Applied Sciences
The combination of neural networks and beamforming has proven very effective in multi-channel speech separation, but its performance faces a challenge in complex environments.
Xu Zhang, Changchun Bao, Xue Yang, Jing Zhou   +3 more
doaj   +1 more source

Distributed Speech Dereverberation Using Weighted Prediction Error

Signal Processing
Speech dereverberation aims to alleviate the negative impact of late reverberant reflections. The weighted prediction error (WPE) method is a well-established technique known for its superior performance in dereverberation. However, in scenarios where microphone nodes are dispersed, the centralized approach of the WPE method requires aggregating all ...
Ziye Yang, Mengfei Zhang, Jie Chen
openaire   +2 more sources

Deep learning based speaker separation and dereverberation can generalize across different languages to improve intelligibility. [PDF]

J Acoust Soc Am, 2021
Healy EW, Johnson EM, Delfarah M, Krishnagiri DS, Sevich VA, Taherian H, Wang D.   +6 more
europepmc   +1 more source

Multi-microphone Complex Spectral Mapping for Utterance-wise and Continuous Speech Separation. [PDF]

IEEE/ACM Trans Audio Speech Lang Process, 2021
Wang ZQ, Wang P, Wang D.
europepmc   +1 more source

A causal and talker-independent speaker separation/dereverberation deep learning algorithm: Cost associated with conversion to real-time capable operation. [PDF]

J Acoust Soc Am, 2021
Healy EW, Taherian H, Johnson EM, Wang D.   +3 more
europepmc   +1 more source

Causal speech enhancement using dynamical-weighted loss and attention encoder-decoder recurrent neural network. [PDF]

PLoS One, 2023
Peracha FK, Khattak MI, Salem N, Saleem N.   +3 more
europepmc   +1 more source