Results 31 to 40 of about 2,562 (160)
Jointly optimal denoising, dereverberation, and source separation
, 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.
Boeddeker, Christoph +5 more
core +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
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
Two-Microphone Dereverberation for Automatic Speech Recognition of Polish
Archives of Acoustics, 2014 Reverberation is a common problem for many speech technologies, such as automatic speech recognition (ASR) systems. This paper investigates the novel combination of precedence, binaural and statistical independence cues for enhancing reverberant speech ...
Mikolaj KUNDEGORSKI +2 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
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
Inverse Filtering and Principal Component Analysis Techniques for Speech Dereverberation
Advances in Electrical and Electronic Engineering, 2016 In this work, we present a single channel approach for early and late reverberation suppression. This approach can be decomposed into two stages. The first stage employs the inverse filter to augment the signal-to-reverberant energy ratio.
Mohamed Anouar Ben Messaoud +1 more
doaj +1 more source
EURASIP Journal on Audio, Speech, and Music Processing, 2021 Many modern smart devices are equipped with a microphone array and a loudspeaker (or are able to connect to one). Acoustic echo cancellation algorithms, specifically their multi-microphone variants, are essential components in such devices.
Nili Cohen +3 more
doaj +1 more source
A unified convolutional beamformer for simultaneous denoising and dereverberation
, 2019 This paper proposes a method for estimating a convolutional beamformer that can perform denoising and dereverberation simultaneously in an optimal way.
Kinoshita, Keisuke, Nakatani, Tomohiro
core +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