Deep-Learning Framework for Efficient Real-Time Speech Enhancement and Dereverberation [PDF]
SensorsDeep learning has revolutionized speech enhancement, enabling impressive high-quality noise reduction and dereverberation. However, state-of-the-art methods often demand substantial computational resources, hindering their deployment on edge devices and ...
Israel Cohen
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Deep Learning-Based Estimation of Reverberant Environment for Audio Data Augmentation [PDF]
Sensors, 2022 This paper proposes an audio data augmentation method based on deep learning in order to improve the performance of dereverberation. Conventionally, audio data are augmented using a room impulse response, which is artificially generated by some methods ...
Deokgyu Yun, Seung Ho Choi
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Joint Optimization of Deep Neural Network-Based Dereverberation and Beamforming for Sound Event Detection in Multi-Channel Environments [PDF]
Sensors, 2020 In this paper, we propose joint optimization of deep neural network (DNN)-supported dereverberation and beamforming for the convolutional recurrent neural network (CRNN)-based sound event detection (SED) in multi-channel environments.
Kyoungjin Noh, Joon-Hyuk Chang
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Cortical adaptation to sound reverberation [PDF]
eLife, 2022 In almost every natural environment, sounds are reflected by nearby objects, producing many delayed and distorted copies of the original sound, known as reverberation.
Aleksandar Z Ivanov +4 more
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A Robust Bilinear Framework for Real-Time Speech Separation and Dereverberation in Wearable Augmented Reality [PDF]
SensorsThis paper presents a bilinear framework for real-time speech source separation and dereverberation tailored to wearable augmented reality devices operating in dynamic acoustic environments.
Alon Nemirovsky +2 more
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Triple-0: Zero-shot denoising and dereverberation on an end-to-end frozen anechoic speech separation network. [PDF]
PLoS ONESpeech enhancement is crucial both for human and machine listening applications. Over the last decade, the use of deep learning for speech enhancement has resulted in tremendous improvement over the classical signal processing and machine learning ...
Sania Gul +2 more
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A dereverberation beamforming algorithm for noise source localization in anechoic and semi-reverberant environments [PDF]
MethodsXThis paper presents a dereverberation beamforming (DBF) technique based on windowing the cross-correlation matrix (CCM) to improve the localization accuracy of beamforming maps for imaging the noise sources generated by real-world applications. Following
R. Singh, A. Mimani, R. Kumar
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Deep Learning Based Target Cancellation for Speech Dereverberation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 DeLiang Wang, Zhong-Qiu Wang
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On the importance of power compression and phase estimation in monaural speech dereverberation [PDF]
JASA 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
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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
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