Results 31 to 40 of about 217 (166)
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
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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
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Speech Dereverberation in the STFT Domain
CoRR, 2015 Reverberation is damaging to both the quality and the intelligibility of a speech signal. We propose a novel single-channel method of dereverberation based on a linear filter in the Short Time Fourier Transform domain. Each enhanced frame is constructed from a linear sum of nearby frames based on the channel impulse response.
Richard Stanton, Mike Brookes
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Amplitude and phase dereverberation of monocomponent signals [PDF]
2017 25th European Signal Processing Conference (EUSIPCO), 2017 Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Arthur Belhomme +3 more
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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
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
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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
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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
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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
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Engineering Reports, Volume 8, Issue 1, January 2026.This workflow presents a complete pipeline for audio data processing, beginning with format conversion, channel adjustments, and cleaning, followed by enhancement and visualization techniques. It further applies signal separation using FastICA, postprocessing, and evaluation metrics (SDR, SIR, SAR) to improve audio analysis and support future research ...
Md. Razu Ahmed +3 more
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