Imperial College London

Dr Patrick A. Naylor

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Speech & Acoustic Signal Processing
 
 
 
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Contact

 

+44 (0)20 7594 6235p.naylor Website

 
 
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Location

 

803Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

328 results found

Thomas MRP, Gudnason J, Naylor PA, Geiser B, Vary Pet al., 2010, Voice Source Estimation for Artificial Bandwidth Extension of Telephone Speech

Conference paper

Habets E, Naylor PA, 2010, An Online Quasi-Newton Algorithm for Blind SIMO Identification

Conference paper

Zhang W, Habets EAP, Naylor PA, 2010, A System Identification-error-robust method for equalization of multichannel acoustic systems

Conference paper

Loganathan P, Habets E, Naylor PA, 2010, Performance Analysis of IPNLMS for Identification of Time-varying System

Conference paper

Castro B, Gaubitch ND, Habets EAP, Gannot S, Naylor PA, Grant Set al., 2010, Subband Scale Factor Ambiguity Correction Using Multiple Filterbanks

Conference paper

Zhang W, Habets EAP, Naylor PA, 2010, On the Use of Channel Shortening in Multichannel Acoustic System Equalization

Conference paper

Thomas MRP, Gaubitch ND, Habets EAP, Naylor PAet al., 2010, Supervised Identification and Removal of Common Filter Components in Adaptive Blind SIMO System Identification

Conference paper

Sharma D, Hilkhuysen G, Gaubitch ND, Naylor PAet al., 2010, Data Driven Method for Non-Intrusive Speech Intelligibility Estimation

Conference paper

Naylor PA, 2010, PROVIDING A PLURALITY OF AUDIO FILES WITH CONSISTENT LOUDNESS LEVELS BUT DIFFERENT AUDIO CHARACTERISTICS

Other

Gudnason J, Thomas MRP, Naylor PA, Ellis DPWet al., 2009, Voice source waveform analysis and synthesis using principal component analysis and Gaussian mixture modelling, Pages: 108-111

The paper presents a voice source waveform modeling techniques based on principal component analysis (PCA) and Gaussian mixture modeling (GMM). The voice source is obtained by inverse-filteirng speech with the estimated vocal tract filter. This decomposition is useful in speech analysis, synthesis, recognition and coding. Existing models of the voice source signal are based on function-fitting or physically motivated assumptions and although they are well defined, estimation of their parameters is not well understood and few are capable of reproducing the large variety of voice source waveforms. Here, a data-driven approach is presented for signal decomposition and classification based on the principal components of the voice source. The principal components are analyzed and the 'prototype' voice source signals corresponding to the Gaussian mixture means are examined. We show how an unknown signal can be decomposed into its components and/or prototypes and resynthesized. We show how the techniques are suited for both low bitrate or high quality analysis/synthesis schemes. Copyright © 2009 ISCA.

Conference paper

Loganathan P, Khong AWH, Naylor PA, 2009, A Class of Sparseness-Controlled Algorithms for Echo Cancellation, IEEE Trans. Audio Speech Language Proc., Vol: 17, Pages: 1591-1601-1591-1601

Journal article

Gaubitch ND, Habets EAP, Naylor PA, 2009, Signal-based Performance Evaluation of Dereverberation Algorithms, Journal of Electrical and Computer Engineering

Journal article

Habets EAP, Benesty J, Gannot S, Naylor PA, Cohen Iet al., 2009, On the Application of the LCMV Beamformer to Speech Enhancement, Pages: 141-144-141-144

Conference paper

Gaubitch ND, Naylor PA, 2009, Equalization of Multichannel Acoustic Systems in Oversampled Subbands, IEEE Trans. Audio Speech Language Proc., Vol: 17, Pages: 1061 - 1070-1061 - 1070

Journal article

Tsakiris MC, Naylor PA, 2009, FAST EXACT AFFINE PROJECTION ALGORITHM USING DISPLACEMENT STRUCTURE THEORY, 16th International Conference on Digital Signal Processing, Publisher: IEEE, Pages: 69-74

Conference paper

Gudnason J, Thomas MRP, Naylor PA, Ellis DPWet al., 2009, Voice Source Waveform Analysis and Synthesis using Principal Component Analysis and Gaussian Mixture Modelling, 10th INTERSPEECH 2009 Conference, Publisher: ISCA-INT SPEECH COMMUNICATION ASSOC, Pages: 120-+

Conference paper

Loganathan P, Lin XS, Khong AWH, Naylor PAet al., 2009, Frequency-domain Adaptive Multidelay Algorithm with Sparseness Control for Acoustic Echo Cancellation

Conference paper

Sharma D, Naylor PA, 2009, Evaluation of Pitch Estimation in Noisy Speech for Application in Non-intrusive Speech Quality Assessment

Conference paper

Thomas MRP, Naylor PA, 2009, The SIGMA Algorithm: A Glottal Activity Detector for Electroglottographic Signals, IEEE Trans. Audio Speech and Language Processing, Vol: 17, Pages: 1557-1566-1557-1566

Journal article

Tsakiris MC, Naylor PA, 2009, Fast exact Affine Projection Algorithm using displacement structure theory, Pages: 1-6-1-6

Conference paper

Wen JYC, Sehr A, Naylor PA, Kellermann Wet al., 2009, Blind Estimation of a Feature-Domain Reverberation Model in Non-diffuse Environments with Variance Adjustment

Conference paper

Zhang W, Khong AWH, Naylor PA, 2009, Acoustic System Equalization using Channel Shortening Techniques for Speech Dereverberation, Pages: 1427-1431-1427-1431

Conference paper

Zhang W, Naylor PA, 2009, An Experimental Study of the Robustness of Multichannel Inverse Filtering Systems to Near-Common Zeros

Conference paper

Thomas MRP, Gudnason J, Naylor PA, 2009, Data-driven voice soruce waveform modelling, Pages: 3965-3968-3965-3968

Conference paper

Gaubitch ND, Brookes M, Naylor PA, 2009, Blind Channel Identification in Speech using the Long-term Average Speech Spectrum

Conference paper

Lin X, Khong AWH, Naylor PA, 2009, Blind system identification for speech dereverberation with Forced Spectral Diversity, Pages: 3737-3740-3737-3740

Conference paper

Thomas MRP, Gudnason J, Naylor PA, 2009, Detection of Glottal Closing and Opening Instants using an Improved DYPSA Framework

Conference paper

Manmontri U, Naylor PA, 2008, A Class of Frobenius Norm-Based Algorithms Using Penalty Term and Natural Gradient for Blind Signal Separation, IEEE Trans. Audio, Speech, and Language Processing, Vol: 16, Pages: 1181-1193-1181-1193

We consider the blind signal separation (BSS) problem of instantaneous mixtures using penalty term and natural gradient. A class of Frobenius norm-based algorithms consisting of the offline/block processing (BP), online processing (OP) algorithms, an.....

Journal article

Gaubitch ND, Habets E, Naylor PA, 2008, Multimicrophone speech dereverberation using spatiotemporal and spectral processing, Pages: 3222-3225-3222-3225

Speech signals acquired in a reverberant room with microphones positioned at a distance from the talker are degraded in quality due to reverberation and measurement noise. Therefore, enhancement of reverberant speech is important in hands-free teleco.....

Conference paper

Zhang W, Khong AWH, Naylor PA, 2008, ADAPTIVE INVERSE FILTERING OF ROOM ACOUSTICS, 42nd Asilomar Conference on Signals, Systems and Computers, Publisher: IEEE, Pages: 788-+, ISSN: 1058-6393

Conference paper

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