Imperial College London
Alternate

Mr Mike Brookes

Faculty of Engineering, Department of Electrical and Electronic Engineering

Emeritus Reader
 
 
 
//

Contact

 

+44 (0)20 7594 6165mike.brookes Website

 
 
//

Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
//

Location

 

807aElectrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Dionelis:2019:10.1109/taslp.2019.2894909,
author = {Dionelis, N and Brookes, D},
doi = {10.1109/taslp.2019.2894909},
journal = {IEEE/ACM Transactions on Audio, Speech and Language Processing},
pages = {799--214},
title = {Modulation-domain Kalman filtering for monaural blind speech denoising and dereverberation},
url = {http://dx.doi.org/10.1109/taslp.2019.2894909},
volume = {27},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We describe a monaural speech enhancement algorithm based on modulation-domain Kalman filtering to blindly track the time-frequency log-magnitude spectra of speech and reverberation. We propose an adaptive algorithm that performs blind joint denoising and dereverberation, while accounting for the inter-frame speech dynamics, by estimating the posterior distribution of the speech log-magnitude spectrum given the log-magnitude spectrum of the noisy reverberant speech. The Kalman filter update step models the non-linear relations between the speech, noise and reverberation log-spectra. The Kalman filtering algorithm uses a signal model that takes into account the reverberation parameters of the reverberation time, T60, and the direct-to-reverberant energy ratio (DRR) and also estimates and tracks the T60 and the DRR in every frequency bin to improve the estimation of the speech log-spectrum. The proposed algorithm is evaluated in terms of speech quality, speech intelligibility and dereverberation performance for a range of reverberation parameters and reverberant speech to noise ratios, in different noises, and is also compared to competing denoising and dereverberation techniques. Experimental results using noisy reverberant speech demonstrate the effectiveness of the enhancement algorithm.
AU  - Dionelis,N
AU  - Brookes,D
DO  - 10.1109/taslp.2019.2894909
EP  - 214
PY  - 2019///
SN  - 2329-9290
SP  - 799
TI  - Modulation-domain Kalman filtering for monaural blind speech denoising and dereverberation
T2  - IEEE/ACM Transactions on Audio, Speech and Language Processing
UR  - http://dx.doi.org/10.1109/taslp.2019.2894909
UR  - https://ieeexplore.ieee.org/document/8624447
UR  - http://hdl.handle.net/10044/1/66975
VL  - 27
ER  -
Download