Results 41 to 50 of about 2,562 (160)
EURASIP Journal on Advances in Signal Processing, 2007 Inverse filtering of room transfer functions (RTFs) is considered an attractive approach for speech dereverberation given that the time invariance assumption of the used RTFs holds.
Masato Miyoshi +2 more
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Signal‐Based Performance Evaluation of Dereverberation Algorithms
Journal of Electrical and Computer Engineering, Volume 2010, Issue 1, 2010., 2010 We address the measurement of reverberation in terms of the (DRR) in the context of the assessment of dereverberation algorithms for which we wish to quantify the level of reverberation before and after processing. The DRR is normally calculated from the impulse response of the reverberating system. However, several important dereverberation algorithms
Patrick A. Naylor +3 more
wiley +1 more source
Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm
, 2018 Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications.
Chen, Fei +5 more
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Speech Dereverberation Using Deep Learning Algorithm
International Journal of Advanced Research in Science, Communication and Technology, 2021 This paper focuses on speech derverberation using a single microphone. We investigate the applicability of fully convolutional networks (FCN) to enhance the speech signal represented by short-time Fourier transform (STFT) images in light of their recent success in many image processing applications.
Dr. S. Saraswathi, S. Ramya
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Reverberant environment embedding using dereverberation autoencoder
Electronics Letters, Volume 61, Issue 1, January/December 2025.We design a neural network architecture for dereverberation, combining linear prediction and dereverberation autoencoder. To improve reverberant speech recognition performance with low computational complexity, we propose a method to extract environmental embedding named DA‐embedding instead of applying dereverberation to the input of an acoustic model.
Sunchan Park, Hyung Soon Kim
wiley +1 more source
Speech Dereverberation with a Reverberation Time Shortening Target
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 This work proposes a new learning target based on reverberation time shortening (RTS) for speech dereverberation. The learning target for dereverberation is usually set as the direct-path speech or optionally with some early reflections. This type of target suddenly truncates the reverberation, and thus it may not be suitable for network training.
Zhou, Rui, Zhu, Wenye, Li, Xiaofei
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IET Signal Processing, Volume 2025, Issue 1, 2025.Active noise control (ANC) algorithms have been developed within the adaptive algorithm framework. However, multichannel ANC systems, which include numerous reference sensors, control speakers, and error microphones, require a very long control filter converging time for control filter estimation.
Hakjun Lee +2 more
wiley +1 more source
Robust Audio Adversarial Example for a Physical Attack
, 2019 We propose a method to generate audio adversarial examples that can attack a state-of-the-art speech recognition model in the physical world. Previous work assumes that generated adversarial examples are directly fed to the recognition model, and is not ...
Sakuma, Jun, Yakura, Hiromu
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Segmentation‐enhanced gamma spectrum denoising based on deep learning
IET Communications, Volume 18, Issue 1, Page 63-80, January 2024.This paper proposes a segmentation‐enhanced convolutional neural network‐stacked denoising autoencoder (CNN‐SDAE) method based on convolutional feature extraction network and stacked denoising autoencoder to achieve gamma spectrum denoising, which adopts the idea of data segmentation to enhance the learning ability of the neural network.
Xiangqun Lu +6 more
wiley +1 more source
IEEE Access, 2019 The accuracy performance of traditional direction of arrival (DOA) estimation algorithms is seriously affected by the reverberation. Considering the advantage of the sparse characteristic of speech signal in time-frequency (T-F) domain, this paper ...
Qiang Fu, Bo Jing, Pengju He
doaj +1 more source