Imperial College London

Mr Mike Brookes

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Signal Processing
 
 
 
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Contact

 

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

 
 
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Assistant

 

Ms Melanie Albright +44 (0)20 7594 6267

 
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Location

 

814Electrical EngineeringSouth Kensington Campus

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Summary

 

Summary

Mike Brookes is a Reader in the Communications and Signal Processing group. After gaining a Mathematics degree from Cambridge, he spent four years at MIT and, later, the University of Hawaii working on the development of telescope systems and astronomical instrumentation. In 1975 he returned to the UK and joined the EEE Dept at Imperial College.

Mike's reseach focuses on speech processing and computer vision. Within the area of speech processing, he has concentrated on the modelling and analysis of speech signals, the extraction of features for speech and speaker recognition and, most recently, on the enhancement of poor quality speech signals. Between 2007 and 2012, he was the Director of the Home Office sponsored Centre for Law Enforcement Audio Research (CLEAR) which investigated techniques for processing heavily corrupted speech signals. In computer vision he led a successful MoD-funded project on radar target recognition in partnership with General Dynamics and Qinetiq and is currently working on a number of computer vision projects concerned with change detection and image-based rendering from multiperspective camera systems.

Mike's teaches courses in mathematics, analysis of circuits, digital signal processing and digital filters.

For more information see http://www.ee.ic.ac.uk/hp/staff/dmb/dmb.html

Selected Publications

Journal Articles

Wang Y, Brookes M, 2018, Model-Based Speech Enhancement in the Modulation Domain, Ieee-acm Transactions on Audio Speech and Language Processing, Vol:26, ISSN:2329-9290, Pages:580-594

Doire CSJ, Brookes M, Naylor PA, 2017, Robust and efficient Bayesian adaptive psychometric function estimation, Journal of the Acoustical Society of America, Vol:141, ISSN:0001-4966, Pages:2501-2512

Doire CSJ, Brookes M, Naylor PA, et al., 2017, Single-Channel Online Enhancement of Speech Corrupted by Reverberation and Noise, Ieee-acm Transactions on Audio Speech and Language Processing, Vol:25, ISSN:2329-9290, Pages:572-587

Naylor, P A, Kounoudes, et al., 2007, Estimation of glottal closure instants in voiced speech using the DYPSA algorithm, IEEE Transactions on Audio Speech and Language Processing, Vol:15, ISSN:1558-7916, Pages:34-43

Gonzalez S, Brookes M, 2014, PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise, Ieee-acm Transactions on Audio Speech and Language Processing, Vol:22, ISSN:2329-9290, Pages:518-530

Hilkhuysen G, Gaubitch N, Brookes M, et al., 2014, Effects of noise suppression on intelligibility. II: An attempt to validate physical metrics, Journal of the Acoustical Society of America, Vol:135, ISSN:0001-4966, Pages:439-450

Gilliam C, Dragotti P-L, Brookes M, 2014, On the Spectrum of the Plenoptic Function, IEEE Transactions on Image Processing, Vol:23, ISSN:1057-7149, Pages:502-516

Hilkhuysen G, Gaubitch N, Brookes M, et al., 2012, Effects of noise suppression on intelligibility: Dependency on signal-to-noise ratios, Journal of the Acoustical Society of America, Vol:131, ISSN:0001-4966, Pages:531-539

Pearson J, Brookes M, Dragotti PL, 2013, Plenoptic Layer-Based Modeling for Image Based Rendering, IEEE Transactions on Image Processing, Vol:22, ISSN:1057-7149, Pages:3405-3419

Gaubitch ND, Brookes M, Naylor PA, 2013, Blind Channel Magnitude Response Estimation in Speech Using Spectrum Classification, IEEE Transactions on Audio Speech and Language Processing, Vol:21, ISSN:1558-7916, Pages:2162-2171

Brookes, M., Naylor, P.A., Gudnason, J., 2006, A quantitative assessment of group delay methods for identifying glottal closures in voiced speech, IEEE Transactions on Audio Speech and Language Processing, Vol:14, ISSN:1558-7916, Pages:456-466

Bouganis C-S, Brookes M, 2007, Statistical multiple light source detection, IET Computer Vision, Vol:1, ISSN:1751-9632, Pages:79-91

More Publications