Jointly Optimal Denoising, Dereverberation, and Source Separation [PDF]
This paper proposes methods that can optimize a Convolutional BeamFormer (CBF) for jointly performing denoising, dereverberation, and source separation (DN+DR+SS) in a computationally efficient way.
Tomohiro Nakatani +2 more
exaly +4 more sources
Deep Learning-Based Estimation of Reverberant Environment for Audio Data Augmentation [PDF]
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
doaj +2 more sources
Joint Optimization of Deep Neural Network-Based Dereverberation and Beamforming for Sound Event Detection in Multi-Channel Environments [PDF]
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
doaj +2 more sources
Deep-Learning Framework for Efficient Real-Time Speech Enhancement and Dereverberation [PDF]
Deep 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 ...
Tomer Rosenbaum +3 more
doaj +2 more sources
Cortical adaptation to sound reverberation [PDF]
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
doaj +2 more sources
A Robust Bilinear Framework for Real-Time Speech Separation and Dereverberation in Wearable Augmented Reality [PDF]
This 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
doaj +2 more sources
A Unified Convolutional Beamformer for Simultaneous Denoising and Dereverberation
This paper proposes a method for estimating a convolutional beamformer that can perform denoising and dereverberation simultaneously in an optimal way.
Tomohiro Nakatani, Keisuke Kinoshita
exaly +3 more sources
A dereverberation beamforming algorithm for noise source localization in anechoic and semi-reverberant environments [PDF]
This 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
doaj +2 more sources
Triple-0: Zero-shot denoising and dereverberation on an end-to-end frozen anechoic speech separation network. [PDF]
Speech 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
doaj +3 more sources
Deep Learning Based Target Cancellation for Speech Dereverberation [PDF]
Zhong-Qiu Wang, DeLiang Wang
exaly +2 more sources

