Results 51 to 60 of about 2,944 (228)
Jointly Optimal Denoising, Dereverberation, and Source Separation [PDF]
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2020 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. Conventionally, cascade configuration composed of a Weighted Prediction Error minimization (WPE) dereverberation filter followed by a Minimum Variance ...
Tomohiro Nakatani +5 more
openaire +2 more sources
BUDDy: Single-Channel Blind Unsupervised Dereverberation with Diffusion Models [PDF]
International Workshop on Acoustic Signal EnhancementIn this paper, we present an unsupervised single-channel method for joint blind dereverberation and room impulse response estimation, based on posterior sampling with diffusion models.
Eloi Moliner +4 more
semanticscholar +1 more source
Single-Channel Speech Enhancement Techniques for Distant Speech Recognition
Journal of Intelligent Systems, 2013 This article presents an overview of the single-channel dereverberation methods suitable for distant speech recognition (DSR) application. The dereverberation methods are mainly classified based on the domain of enhancement of speech signal captured by a
Ashwini Jaya Kumar +1 more
doaj +1 more source
EURASIP Journal on Audio, Speech, and Music Processing, 2023 More and more smart home devices with microphones come into our life in these years; it is highly desirable to connect these microphones as wireless acoustic sensor networks (WASNs) so that these devices can be better controlled in an enclosure.
Zhe Han +3 more
doaj +1 more source
Expectation‐maximisation for speech source separation using convolutive transfer function
CAAI Transactions on Intelligence Technology, Volume 4, Issue 1, Page 47-53, March 2019., 2019 This study addresses the problem of under‐determined speech source separation from multichannel microphone signals, i.e. the convolutive mixtures of multiple sources. The time‐domain signals are first transformed to the short‐time Fourier transform (STFT) domain.
Xiaofei Li, Laurent Girin, Radu Horaud
wiley +1 more source
Tracking of Moving Sources in a Reverberant Environment Using Evolutionary Algorithms
IEEE Access, 2022 This paper describes a source tracking technique in a reverberant environment using a new combination of an adaptive species-based particle swarm optimization (ASPSO) algorithm and a multiple signal classification (MUSIC) algorithm.
Mingsian R. Bai +2 more
doaj +1 more source
Deep Learning Methods for Underwater Target Feature Extraction and Recognition
Computational Intelligence and Neuroscience, Volume 2018, Issue 1, 2018., 2018 The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert‐Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction.
Gang Hu +6 more
wiley +1 more source
De-Noising Process in Room Impulse Response with Generalized Spectral Subtraction
Applied Sciences, 2021 The generalized spectral subtraction algorithm (GBSS), which has extraordinary ability in background noise reduction, is historically one of the first approaches used for speech enhancement and dereverberation. However, the algorithm has not been applied
Min Chen, Chang-Myung Lee
doaj +1 more source
Noisy Reverberation Suppression Using AdaBoost Based EMD in Underwater Scenario
International Journal of Oceanography, Volume 2014, Issue 1, 2014., 2014 Reverberation suppression is a crucial problem in sonar communications. If the acoustic signal is radiated in the water as medium then the degradation is caused due to the reflection coming from surface, bottom, and volume of water. This paper presents a novel signal processing scheme that offers an improved solution in reducing the effect of ...
Kusma Kumari Cheepurupalli +2 more
wiley +1 more source
Blind‐Matched Filtering for Speech Enhancement with Distributed Microphones
Journal of Electrical and Computer Engineering, Volume 2012, Issue 1, 2012., 2012 A multichannel noise reduction and equalization approach for distributed microphones is presented. The speech enhancement is based on a blind‐matched filtering algorithm that combines the microphone signals such that the output SNR is maximized. The algorithm is developed for spatially uncorrelated but nonuniform noise fields, that is, the noise ...
Sebastian Stenzel +2 more
wiley +1 more source