Results 21 to 30 of about 215 (163)

Subspace Methods for Multimicrophone Speech Dereverberation [PDF]

open access: yesEURASIP Journal on Advances in Signal Processing, 2003
A novel approach for multimicrophone speech dereverberation is presented. The method is based on the construction of the null subspace of the data matrix in the presence of colored noise, using the generalized singular-value decomposition (GSVD ...
Moonen Marc, Gannot Sharon
doaj   +2 more sources

Deep Learning Based Target Cancellation for Speech Dereverberation [PDF]

open access: yesIEEE/ACM Transactions on Audio Speech and Language Processing, 2020
Zhong-Qiu Wang, Deliang Wang
exaly   +2 more sources

On the importance of power compression and phase estimation in monaural speech dereverberation [PDF]

open access: yesJASA Express Letters, 2021
Previous studies have shown the importance of introducing power compression on both feature and target when only the magnitude is considered in the dereverberation task.
Andong Li   +3 more
doaj   +1 more source

Jointly Optimal Dereverberation and Beamforming [PDF]

open access: yesICASSP 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 Böddeker   +3 more
openaire   +2 more sources

Effective Dereverberation with a Lower Complexity at Presence of the Noise

open access: yesApplied 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

open access: yesEURASIP 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

open access: yesMethods 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

Head‐related transfer function–reserved time‐frequency masking for robust binaural sound source localization

open access: yesCAAI Transactions on Intelligence Technology, Volume 7, Issue 1, Page 26-33, March 2022., 2022
Abstract Various time‐frequency (T‐F) masks are being applied to sound source localization tasks. Moreover, deep learning has dramatically advanced T‐F mask estimation. However, existing masks are usually designed for speech separation tasks and are suitable only for single‐channel signals.
Hong Liu   +4 more
wiley   +1 more source

A Multi-Source Separation Approach Based on DOA Cue and DNN

open access: yesApplied Sciences, 2022
Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is ...
Yu Zhang   +3 more
doaj   +1 more source

[Retracted] Serialized Recommendation Technology Based on Deep Neural Network

open access: yesWireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022
Since the construction of brain network is like organic brain organization, profound brain network has high effectiveness and high accuracy in separating data from profound elements, fit for multifacet learning, conceptual component portrayal, cross‐space learning capacity, multisource, heterogeneous data content.
Long Jin, Chia-Huei Wu
wiley   +1 more source

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