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Conference paperHu M, Parada PP, Sharma D, et 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 paperDoire CSJ, Brookes M, Naylor PA, et 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 paperSharma D, Poddar A, Manna S, et 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 articleLim F, Zhang W, Habets EAP, et al., 2014,
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 paperEvers C, Moore AH, Naylor PA, 2014,
Multiple source localisation in the spherical harmonic domain
Conference paperMoore 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 paperEaton 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 articleJarrett DP, Taseska M, Habets EAP, et 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 paperEaton J, Naylor PA, 2014,
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 paperStanton R, Gaubitch N, Naylor P, et 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 paperAntonello N, van Waterschool T, Moonen M, et 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 paperCosta 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 paperParada PP, Sharma D, Naylor PA, 2014,
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 paperZahedi A, Østergaard J, Jensen SH, et al., 2014,
In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node's measurement and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighbouring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly encoding multiple sources. We focus on the case where node measurements are in form of noisy linearly mixed combinations of the sources and the acoustic channel mixing matrices are invertible. For this problem, we derive the rate-distortion function for vector Gaussian sources and under covariance distortion constraints. © 2014 IEEE.
Conference paperSharma D, Meredith L, Lainez J, et al., 2014,
A Non-Intrusive PESQ Measure, IEEE Global Conference on Signal and Information Processing (GlobalSIP), Publisher: IEEE, Pages: 975-978
Conference paperParada PP, Sharma D, Naylor PA, et al., 2014,
REVERBERANT SPEECH RECOGNITION: A PHONEME ANALYSIS, IEEE Global Conference on Signal and Information Processing (GlobalSIP), Publisher: IEEE, Pages: 567-571
Conference paperZahedi A, Ostergaard J, Jensen SH, et al., 2014,
Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 586-590
Conference paperThomas MRP, Tashev IJ, Lim F, et al., 2014,
OPTIMAL BEAMFORMING AS A TIME DOMAIN EQUALIZATION PROBLEM WITH APPLICATION TO ROOM ACOUSTICS, 14th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE, Pages: 75-79
Conference paperLim F, Naylor PA, 2014,
STATISTICAL MODELLING OF MULTICHANNEL BLIND SYSTEM IDENTIFICATION ERRORS, 14th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE, Pages: 119-123
Conference paperParada PP, Sharma D, Lainez J, et al., 2014,
A QUANTITATIVE COMPARISON OF BLIND C-50 ESTIMATORS, 14th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE, Pages: 298-302
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