Dereverberation in Acoustic Sensor Networks Using Weighted Prediction Error With Microphone-dependent Prediction Delays [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023 In the last decades several multi-microphone speech dereverberation algorithms have been proposed, among which the weighted prediction error (WPE) algorithm.
Anselm Lohmann +3 more
openalex +3 more sources
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 +3 more sources
Jointly Optimal Dereverberation and Beamforming [PDF]
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 We previously proposed an optimal (in the maximum likelihood sense) convolutional beamformer that can perform simultaneous denoising and dereverberation, and showed its superiority over the widely used cascade of a WPE dereverberation filter and a conventional MPDR beamformer.
Christoph Boeddeker +3 more
openalex +4 more sources
Speech Enhancement and Dereverberation With Diffusion-Based Generative Models [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2022 In this work, we build upon our previous publication and use diffusion-based generative models for speech enhancement. We present a detailed overview of the diffusion process that is based on a stochastic differential equation and delve into an extensive
Julius Richter +4 more
semanticscholar +1 more source
The Journal of the Acoustical Society of America, 1973 A method for dereverberating speech based on linear prediction is developed in detail. By properly analyzing and resynthesizing speech that has been reverberated by a real room, it is possible to remove most of the reverberation. The algorithm will be described and tapes will be played.
J. B. Allen
openalex +3 more sources
SpatialNet: Extensively Learning Spatial Information for Multichannel Joint Speech Separation, Denoising and Dereverberation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2023 This work proposes a neural network to extensively exploit spatial information for multichannel joint speech separation, denoising and dereverberation, named SpatialNet. In the short-time Fourier transform (STFT) domain, the proposed network performs end-
Changsheng Quan, Xiaofei Li
semanticscholar +1 more source
StoRM: A Diffusion-Based Stochastic Regeneration Model for Speech Enhancement and Dereverberation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2022 Diffusion models have shown a great ability at bridging the performance gap between predictive and generative approaches for speech enhancement. We have shown that they may even outperform their predictive counterparts for non-additive corruption types ...
Jean-Marie Lemercier +3 more
semanticscholar +1 more source
Effective Dereverberation with a Lower Complexity at Presence of the Noise
Applied Sciences, 2022 Adaptive beamforming and deconvolution techniques have shown effectiveness for reducing noise and reverberation. The minimum variance distortionless response (MVDR) beamformer is the most widely used for adaptive beamforming, whereas multichannel linear ...
Fengqi Tan, Changchun Bao, Jing Zhou
doaj +1 more source
A neural network-supported two-stage algorithm for lightweight dereverberation on hearing devices
EURASIP Journal on Audio, Speech, and Music Processing, 2023 A two-stage lightweight online dereverberation algorithm for hearing devices is presented in this paper. The approach combines a multi-channel multi-frame linear filter with a single-channel single-frame post-filter.
Jean-Marie Lemercier +3 more
doaj +1 more source
pykanto: A python library to accelerate research on wild bird song
Methods in Ecology and Evolution, Volume 14, Issue 8, Page 1994-2002, August 2023., 2023 Abstract Studying the vocalisations of wild animals can be a challenge due to the limitations of traditional computational methods, which often are time‐consuming and lack reproducibility. Here, I present pykanto, a new software package that provides a set of tools to build, manage, and explore large sound databases.
Nilo Merino Recalde
wiley +1 more source