Publications

@inproceedings{Thomas2008c,
title = {The SIGMA Algorithm for Estimation of Reference-Quality Glottal Closure Instants from Electroglottograph Signals},
author = {M R P Thomas and P A Naylor},
url = {http://ieeexplore.ieee.org/document/7080348/},
year = {2008},
date = {2008-08-01},
booktitle = {Proc. European Signal Processing Conf. (EUSIPCO)},
address = {Lausanne, Switzerland},
abstract = {Accurate estimation of glottal closure instants (GCIs) in voiced speech is important for speech analysis applications which benefit from glottal-synchronous processing. Electroglottograph (EGG) recordings give a measure of the electrical conductance of the glottis, providing a signal which is proportional to its contact area. EGG signals contain little noise or distortion, providing a good reference from which GCIs can be extracted to evaluate GCI estimation from speech recordings. Many approaches impose a threshold on the differentiated EGG signal which provide accurate results during voiced speech but are prone to errors at the onset and end of voicing; modern algorithms use a similar approach across multiple dyadic scales using the stationary wavelet transform. This paper describes a new method for EGG-based GCI estimation named SIGMA, which is based upon the stationary wavelet transform, peak detection with a group delay function and Gaussian Mixture Modelling for discrimination between true and false GCI candidates. In most real-world environments, it is necessary to estimate GCIs from a speech signal recorded with a microphone placed at some distance from the talker. The presence of reverberation, noise and filtering by the vocal tract render GCI detection from real speech signals relatively difficult to achieve compared with the EGG, so EGG-based references have often been used to evaluate GCI detection from speech signals. Evaluation against 500 hand-labelled sentences has shown an accuracy of 99.35%, a 4.7% improvement over a popular existing method.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Gaubitch2007a,
title = {Subband Method for Multichannel Least Squares Equalization of Room Transfer Functions},
author = {N D Gaubitch and M R P Thomas and P A Naylor},
url = {http://ieeexplore.ieee.org/document/4392981/},
year = {2007},
date = {2007-10-01},
booktitle = {Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics},
address = {New Paltz, New York},
abstract = {Equalization of room transfer functions (RTFs) is important in many speech and audio processing applications. It is a challenging problem because RTFs are several thousand taps long and non-minimum phase and in practice only approximate measurements of the RTFs are available. In this paper, we present a subband multichannel least squares method for equalization of RTFs which is computationally efficient and less sensitive to inaccuracies in the measured RTFs compared to its fullband counterpart. Experimental results using simulated impulse responses demonstrate the performance of the algorithm.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Thomas2007b,
title = {A Practical Multichannel Dereverberation Algorithm Using Multichannel DYPSA and Spatiotemporal Averaging},
author = {M R P Thomas and N D Gaubitch and J Gudnason and P A Naylor},
url = {http://ieeexplore.ieee.org/document/4392983/},
year = {2007},
date = {2007-10-01},
booktitle = {Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics},
address = {New Paltz, NY},
abstract = {Speech signals for hands-free telecommunication applications are received by one or more microphones placed at some distance from the talker. In an office environment, for example, unwanted signals such as reverberation and background noise from computers and other talkers will degrade the quality of the received signal. These unwanted components have an adverse effect upon speech processing algorithms and impair intelligibility. This paper demonstrates the use of the Multichannel DYPSA algorithm to identify glottal closure instants (GCIs) from noisy, reverberant speech. Using the estimated GCIs, a spatiotemporal averaging technique is applied to attenuate the unwanted components. Experiments with a microphone array demonstrate the dereverberation and noise suppression of the spatiotemporal averaging method, showing up to a 5 dB improvement in segmental SNR and 0.33 in normalized Bark spectral distortion score.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Thomas2007a,
title = {Multichannel DYPSA for estimation of glottal closure instants in reverberant speech},
author = {M R P Thomas and N D Gaubitch and P A Naylor},
url = {http://ieeexplore.ieee.org/document/7099170/},
year = {2007},
date = {2007-09-01},
booktitle = {Proc. European Signal Processing Conf. (EUSIPCO)},
address = {Poznan, Poland},
abstract = {Identification of glottal closure instants (GCIs) is important in speech applications which benefit from larynx-synchronous processing. In modern telecommunication applications, speech signals are often obtained inside office rooms, with one or more microphones placed at a distance from the talker. Such speech signals are affected by reverberation due to the reflections from surrounding walls and objects, which distort the observed speech signals and degrade the performance of speech processing algorithms. This paper presents a study of the identifiability of GCIs from reverberant speech using the Dynamic Programming Projected Phase-Slope Algorithm (DYPSA) and new extensions to the multimicrophone case. Two multichannel algorithms are proposed and evaluated; in both cases, considerable performance gains over a single microphone are obtained, with detection rates improved by up to 29% in highly reverberant environments.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}