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  • Conference paper
    Hafezi S, Moore AH, Naylor PA, 2015,

    MODELING SOURCE DIRECTIVITY IN ROOM IMPULSE RESPONSE SIMULATION FOR SPHERICAL MICROPHONE ARRAYS

    , 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 574-578, ISSN: 2076-1465
  • Conference paper
    Nelke CM, Naylor PA, Vary P, 2015,

    CORPUS BASED RECONSTRUCTION OF SPEECH DEGRADED BY WIND NOISE

    , 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 864-868, ISSN: 2076-1465
  • Conference paper
    Javed HA, Naylor PA, 2015,

    AN EXTENDED REVERBERATION DECAY TAIL METRIC AS A MEASURE OF PERCEIVED LATE REVERBERATION

    , 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 1063-1067, ISSN: 2076-1465
  • Conference paper
    Cauchi B, Naylor PA, Gerkmann T, Doclo S, Goetze Set al., 2015,

    LATE REVERBERANT SPECTRAL VARIANCE ESTIMATION USING ACOUSTIC CHANNEL EQUALIZATION

    , 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 2481-2485, ISSN: 2076-1465
  • Conference paper
    Antonello N, van Waterschoot T, Moonen M, Naylor PAet al., 2015,

    Evaluation of a numerical method for identifying surface acoustic impedances in a reverberant room

    , Pages: 185-190

    Wave-based room acoustic simulations are becoming more popular as the available compute power continues to increase. The definition of boundary conditions and acoustic impedances is of fundamental importance for these simulations to succeed in representing a realistic acoustical space. Acoustic impedance databases exist in terms of absorption coefficients, which are usually measured in reverberation chambers. In this type of measurements, the sound field is assumed to be diffuse, a condition which is not met in most rooms. In particular at low frequencies, where wave-based simulations are possible, a different approach is sought as an alternative to acoustic impedance measurements. This paper focuses on a recently proposed method for estimating surface acoustic impedances. This method is based on the use of a numerical room model, and does not require the assumption of a diffuse field. Assuming that the geometry of the room is known, a finite difference time domain (FDTD) simulation is matched with measured data by solving an optimization problem. The set-up for such a measurement method consists only of a set of microphones and a loudspeaker. This could be applied in every room, removing the need for expensive facilities such as reverberation chambers. The solution of the optimization problem leads to the sought parameters of the acoustic surface impedances. In this paper the adjoint method is used for the computation of the derivative in the optimization problem. This method enables a large number of decision variables in the optimization problem making it possible to account for inhomogeneities of the surface acoustic impedance and hence to avoid the need to specify the different acoustic impedance surfaces beforehand.
  • Conference paper
    Lim F, Naylor PA, Thomas MRP, Tashev IJet al., 2015,

    ACOUSTIC BLUR KERNEL WITH SLIDING WINDOW FOR BLIND ESTIMATION OF REVERBERATION TIME

    , IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), Publisher: IEEE, ISSN: 1931-1168
  • Conference paper
    Hu M, Parada PP, Sharma D, Doclo S, van Waterschoot T, Brookes M, Naylor PAet al., 2015,

    SINGLE-CHANNEL SPEAKER DIARIZATION BASED ON SPATIAL FEATURES

    , IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), Publisher: IEEE, ISSN: 1931-1168
  • Conference paper
    Doire CSJ, Brookes M, Naylor PA, Betts D, Hicks CM, Dmour MA, Jensen SHet al., 2015,

    SINGLE-CHANNEL BLIND ESTIMATION OF REVERBERATION PARAMETERS

    , 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 31-35, ISSN: 1520-6149
  • Conference paper
    Sharma D, Poddar A, Manna S, Naylor PAet al., 2015,

    THE SAS PROJECT: SPEECH SIGNAL PROCESSING IN HIGH SCHOOL EDUCATION

    , 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 1781-1785, ISSN: 2076-1465
  • Journal article
    Lim F, Zhang W, Habets EAP, Naylor PAet al., 2014,

    Robust multichannel dereverberation using relaxed multichannel least squares

    , IEEE ACM Transactions on Audio, Speech, and Language Processing, Vol: 22, Pages: 1379-1390, ISSN: 1558-7916

    A novel approach is proposed for robust multichannel dereverberation in the presence of system identification error (SIEs), based on channel shortening. A mathematical link is derived between the well known multiple-input/output inverse theorem (MINT) algorithm and channel shortening. The relaxed multichannel least squares (RMCLS) algorithm is then proposed as an efficient realization within the channel shortening paradigm and is shown through experimental results to outperform MINT in the presence of SIEs. While the RMCLS is robust to SIEs, the coloration of the output cannot be controlled. Two extensions to RMCLS are proposed to control the level of coloration and the performances of both extensions are evaluated comparatively. It is shown that both substantially maintain the dereverberation performance and robustness to SIEs obtained from RMCLS while effectively controlling the level of coloration introduced.
  • Conference paper
    Evers C, Moore AH, Naylor PA, 2014,

    Multiple source localisation in the spherical harmonic domain
  • Conference paper
    Moore AH, Naylor PA, Skoglund J, 2014,

    An Analysis of the Effect of Larynx-Synchronous Averaging on Dereverberation of Voiced Speech

    , European Signal Processing Conference, ISSN: 2219-5491
  • Conference paper
    Eaton J, Naylor PA, 2014,

    Detection of clipping in coded speech signals

    , 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE

    In order to exploit the full dynamic range of communicationsand recording equipment, and to minimise the effects of noiseand interference, input gain to a recording device is typicallyset as high as possible. This often leads to the signal exceedingthe input limit of the equipment resulting in clipping. Com-munications devices typically rely on codecs such as GSM06.10to compress voice signals into lower bitrates. Althoughdetecting clipping in a hard-clipped speech signal is straight-forward due to the characteristic flattening of the peaks of thewaveform, this is not the case for speech that has subsequentlypassed through a codec. We describe a novel clipping detec-tion algorithm based on amplitude histogram analysis and leastsquares residuals which can estimate the clipped samples andthe original signal level in speech even after the clipped speechhas been perceptually coded.
  • Journal article
    Jarrett DP, Taseska M, Habets EAP, Naylor PAet al., 2014,

    Noise Reduction in the Spherical Harmonic Domain Using a Tradeoff Beamformer and Narrowband DOA Estimates

    , IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol: 22, Pages: 965-976
  • Conference paper
    Eaton J, Naylor PA, 2014,

    Noise-robust detection of peak-clipping in decoded speech

    , Pages: 7019-7023

    Clipping is a commonplace problem in voice telecommunications and detection of clipping is useful in a range of speech processing applications. We analyse and evaluate the performance of three previously presented algorithms for clipping detection in decoded speech in high levels of ambient noise. We identify a baseline method which is well known for clipping detection, determine experimentally the optimized operation parameter for the baseline approach, and use this in our experiments. Our results indicate that the new algorithms outperform the baseline except at extreme levels of clipping and negative signal-to-noise ratios.
  • Conference paper
    Stanton R, Gaubitch N, Naylor P, Brookes DMet al., 2014,

    A Differentiable Approximation to Speech Intelligibility Index with Applications to Listening Enhancement

    , AES Intl Conf on Audio Forensics

    The Speech Intelligibility Index is a standardised objective measure for estimating the intelligibility of speech in noise. It is, however difficult to use it in the iterative optimisation of speech enhancement algorithms because it is a discontinuous function of its input parameters. In this paper, we derive an approximation for the Speech Intelligibility Index that is both continuous and differentiable, which allows for more efficient optimisation procedures. The use of the approximation is demonstrated in an application to near-end speech enhancement.
  • Conference paper
    Antonello N, van Waterschool T, Moonen M, Naylor PAet al., 2014,

    SOURCE LOCALIZATION AND SIGNAL RECONSTRUCTION IN A REVERBERANT FIELD USING THE FDTD METHOD

    , 22nd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 301-305, ISSN: 2076-1465
  • Conference paper
    Costa MH, Naylor PA, 2014,

    ILD PRESERVATION IN THE MULTICHANNEL WIENER FILTER FOR BINAURAL HEARING AID APPLICATIONS

    , 22nd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 636-640, ISSN: 2076-1465
  • Conference paper
    Parada PP, Sharma D, Naylor PA, 2014,

    Non-intrusive estimation of the level of reverberation in speech

    , Pages: 4718-4722, ISSN: 1520-6149

    We show corroborating evidence that, among a set of common acoustic parameters, the clarity index C50 provides a measure of reverberation that is well correlated with speech recognition accuracy. We also present a data driven method for non-intrusive C50 parameter estimation from a single channel speech signal. The method extracts a number of features from the speech signal and uses a binary regression tree, trained on appropriate training data, to estimate the C50. Evaluation is carried out using speech utterances convolved with real and simulated room impulse responses, and additive babble noise. The new method outperforms a baseline approach in our evaluation. © 2014 IEEE.
  • Conference paper
    Zahedi A, Ostergaard J, Jensen SH, Naylort P, Bech Set al., 2014,

    Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

    , Data Compression Conference (DCC), Publisher: IEEE COMPUTER SOC, Pages: 263-272, ISSN: 1068-0314

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