2012 |
T Drugman; M R P Thomas; J Gudnason; T Dutoit; P A Naylor Detection of Glottal Closing Instants from Voiced Speech: A Quantitative Review Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 20, no. 3, pp. 994–1006, 2012. @article{Drugman2012,The pseudo-periodicity of voiced speech can be exploited in several speech processing applications. This requires however that the precise locations of the glottal closure instants (GCIs) are available. The focus of this paper is the evaluation of automatic methods for the detection of GCIs directly from the speech waveform. Five state-of-the-art GCI detection algorithms are compared using six different databases with contemporaneous electroglottographic recordings as ground truth, and containing many hours of speech by multiple speakers. The five techniques compared are the Hilbert Envelope-based detection (HE), the Zero Frequency Resonator-based method (ZFR), the Dynamic Programming Phase Slope Algorithm (DYPSA), the Speech Event Detection using the Residual Excitation And a Mean-based Signal (SEDREAMS) and the Yet Another GCI Algorithm (YAGA). The efficacy of these methods is first evaluated on clean speech, both in terms of reliabililty and accuracy. Their robustness to additive noise and to reverberation is also assessed. A further contribution of the paper is the evaluation of their performance on a concrete application of speech processing: the causal-anticausal decomposition of speech. It is shown that for clean speech, SEDREAMS and YAGA are the best performing techniques, both in terms of identification rate and accuracy. ZFR and SEDREAMS also show a superior robustness to additive noise and reverberation. |
F Antonacci; J Filos; E A P Habets; A Sarti; P A Naylor; S Tubaro Inference of Room Geometry from Acoustic Impulse Responses Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., 2012. @article{Antonacci2012,Acoustic scene reconstruction is a process that aims to infer characteristics of the environment from acoustic measurements. We investigate the problem of locating planar reflectors in rooms, such as walls and furniture, from signals obtained using distributed microphones. Specifically, localization of multiple two- dimensional (2-D) reflectors is achieved by estimation of the time of arrival (TOA) of reflected signals by analysis of acoustic impulse responses (AIRs). The estimated TOAs are converted into elliptical constraints about the location of the line reflector, which is then localized by combining multiple constraints. When multiple walls are present in the acoustic scene, an ambiguity problem arises, which we show can be addressed using the Hough transform. Additionally, the Hough transform significantly improves the robustness of the estimation for noisy measurements. The proposed approach is evaluated using simulated rooms under a variety of different controlled conditions where the floor and ceiling are perfectly absorbing. Results using AIRs measured in a real environment are also given. Additionally, results showing the robustness to additive noise in the TOA information are presented, with particular reference to the improvement achieved through the use of the Hough transform. |
M R P Thomas; J Gudnason; P A Naylor Estimation of Glottal Closing and Opening Instants in Voiced Speech using the YAGA Algorithm Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 20, no. 1, pp. 82–91, 2012. @article{Thomas2012a,Accurate estimation of glottal closing instants (GCIs) and opening instants (GOIs) is important for speech processing applications that benefit from glottal-synchronous processing including pitch tracking, prosodic speech modification, speech dereverberation, synthesis and study of pathological voice. We propose the Yet Another GCI/GOI Algorithm (YAGA) to detect GCIs from speech signals by employing multiscale analysis, the group delay function, and N-best dynamic programming. A novel GOI detector based upon the consistency of the candidates' closed quotients relative to the estimated GCIs is also presented. Particular attention is paid to the precise definition of the glottal closed phase, which we define as the analysis interval that produces minimum deviation from an all-pole model of the speech signal with closed-phase linear prediction (LP). A reference algorithm analyzing both electroglottograph (EGG) and speech signals is described for evaluation of the proposed speech-based algorithm. In addition to the development of a GCI/GOI detector, an important outcome of this work is in demonstrating that GOIs derived from the EGG signal are not necessarily well-suited to closed-phase LP analysis. Evaluation of YAGA against the APLAWD and SAM databases show that GCI identification rates of up to 99.3% can be achieved with an accuracy of 0.3 ms and GOI detection can be achieved equally reliably with an accuracy of 0.5 ms. |
2011 |
A Canclini; F Antonacci; M R P Thomas; J Filos; A Sarti; P A Naylor; S Tubaro Exact Localization of Acoustic Reflectors from Quadratic Constraints Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, 2011. @inproceedings{Canclini2011,In this paper we discuss a method for localizing acoustic reflectors in space based on acoustic measurements on source-to-microphone reflective paths. The method converts Time of Arrival (TOA) and Time Difference of Arrival (TDOA) into quadratic constraints on the line corresponding to the reflector. In order to be robust against measurement errors we derive an exact solution for the minimization of a cost function that combines an arbitrary number of quadratic constraints. Moreover we propose a new method for the analytic prediction of reflector localization accuracy. This method is sufficiently general to be applicable to a wide range of estimation problems. |
M R P Thomas; N D Gaubitch; P A Naylor Application of Channel Shortening to Acoustic Channel Equalization in the Presence of Noise and Estimation Error Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, USA, 2011. @inproceedings{Thomas2011,The inverse-filtering of acoustic impulse responses (AIRs) can be achieved with existing methods provided a good estimate of the channel is available and the observed signals contain little or no noise. Such assumptions are not generally valid in practical scenarios, leading to much interest in the issue of robustness. In particular, channel shortening (CS) techniques have been shown to be more robust to channel estimation error than existing approaches. In this paper we investigate CS using the relaxed multichannel least-squares (RMCLS) algorithm in the presence of both channel error and additive noise. It is shown quantitatively that shortening the acoustic channel to a few ms duration is more robust than attempting to equalize the channel fully, giving better resultant sound quality for dereverberation. A key point of this paper is to provide an explanation for this added robustness in terms of the equalization filter gain. We provide simulation results and results for practical settings using speech recordings and room impulse response measurements from a real acoustic environment. |
P Annibale; F Antonacci; P Bestagini; A Brutti; A Canclini; L Cristoforetti; E A P Habets; J Filos; W Kellermann; K Kowalczyk; A Lombard; E Mabande; D Markovic; P A Naylor; M Omologo; R Rabenstein; Sarti A P Svaizer; M R P Thomas The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensing and Rendering Proceedings Article In: Proc. Audio Eng. Soc. Convention, New York, 2011. @inproceedings{Sarti2011,SCENIC is an EC-funded project aimed at developing a harmonized corpus of methodologies for environment-aware acoustic sensing and rendering. The project focusses on space-time acoustic processing solutions that do not just accommodate the environment in the modeling process but that make the environment help towards achieving the goal at hand. The solutions developed within this project cover a wide range of applications, including acoustic self-calibration, aimed at estimating the parameters of the acoustic system; environment inference, aimed at identifying and characterizing all the relevant acoustic reflectors in the environment. The information gathered through such steps is then used to boost the performance of wavefield rendering methods as well as source localization/characterization/extraction in reverberant environments. |
D P Jarrett; E A P Habets; M R P Thomas; P A Naylor Simulating Room Impulse Responses for Spherical Microphone Arrays Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2011. @inproceedings{Jarrett2011b,A method is proposed for simulating the sound pressure signals on a spherical microphone array in a reverberant enclosure. The method employs spherical harmonic decomposition and takes into account scattering from a solid sphere. An analysis shows that the error in the decomposition can be made arbitrarily small given a sufficient number of spherical harmonics. |
J Filos; A Canclini; M R P Thomas; F Antonacci; A Sarti; P A Naylor Robust Inference of Room Geometry from Acoustic Impulse Responses Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Barcelona, Spain, 2011. @inproceedings{Filos2011,The problem of localizing reflective boundaries in an acoustic environment from acoustic measurements is considered. Specifically, localization of multiple two-dimensional (2-D) line reflectors is achieved by estimation of the time of arrival (TOA) of reflected signals by analysis of acoustic impulse responses (AIRs). The estimated TOAs are used in conjunction with the source and receiver locations to find the loci of solutions whose common tangents correspond to the location of a reflector. The solution to the common tangent estimation is a nonlinear and non-convex problem that can yield local sub-optimal solutions using existing approaches. We therefore propose an analytic method, based on a closed-form estimator, that is guaranteed to converge to the global minimum in an error-free scenario. We further improve the robustness of the approach when errors are introduced in the estimated TOAs by using the Hough transform to find the optimal solution. The proposed approach is evaluated through Monte Carlo runs, using simulated rooms, that demonstrate the feasibility of the proposed approach. |
J Gudnason; M R P Thomas; D P W Ellis; P A Naylor Data-Driven Voice Source Waveform Analysis and Synthesis Journal Article In: Speech Communication, vol. 54, no. 2, pp. 199–211, 2011. @article{Gudnason2011,A data-driven approach is introduced for studying, analyzing and processing the voice source signal. Existing approaches parameterize the voice source signal by using models that are motivated, for example, by a physical model or function-fitting. Such parameterization is often difficult to achieve and it produces a poor approximation to a large variety of real voice source waveforms of the human voice. This paper presents a novel data-driven approach to analyze different types of voice source waveforms using principal component analysis and Gaussian mixture modeling. This approach models certain voice source features that many other approaches fail to model. Prototype voice source waveforms are obtained from each mixture component and analyzed with respect to speaker, phone and pitch. An analysis/synthesis scheme was set up to demonstrate the effectiveness of the method. Compression of the proposed voice source by discarding 75% of the features yields a segmental signal-to-reconstruction error ratio of 13 dB and a Bark spectral distortion of 0.14. |
D P Jarrett; E A P Habets; M R P Thomas; N D Gaubitch; P A Naylor Dereverberation Performance of Rigid and Open Spherical Microphone Arrays: Theory & Simulation Proceedings Article In: Proc. Joint Workshop on Hands-Free Speech Communication and Microphone Arrays (HSCMA), Edinburgh, UK, 2011. @inproceedings{Jarrett2011b,Linear microphone arrays have been extensively used for dereverberation. In this paper we look at the dereverberation performance of two types of spherical microphone array: the open array (microphones suspended in free space) and the rigid array (microphones mounted on a rigid baffle). Dereverberation is performed in the spherical harmonic domain using a technique similar to the commonly used delay-and-sum beamformer (DSB). We analyse the theoretical performance with respect to the direct-to-reverberant ratio (DRR), and we also present simulation results obtained using a simulation tool for spherical arrays. The performance of the spherical DSB is found to increase with the radius of the sphere, and to be 1-2 dB higher for the rigid array. These results serve as a baseline for evaluating the performance of future dereverberation algorithms for spherical arrays. |
2010 |
M R P Thomas; N D Gaubitch; E A P Habets; P A Naylor Supervised Identification and Removal of Common Filter Components in Adaptive Blind SIMO System Identification Proceedings Article In: Proc. Intl. Workshop Acoust. Echo Noise Control (IWAENC), Tel Aviv, Israel, 2010. @inproceedings{Thomas2010b,Adaptive blind system identification with LMS-type algorithms is prone to misconvergence in the presence of noise. In this paper we consider the hypothesis that such misconvergence is due to the introduction of a common filter to the estimated impulse respones. A technique is presented for identifying and removing the common filter using prior knowledge of the true channels. Experimental results with this approach show an improved rate of convergence and reduced system error. Furthermore, misconvergent behaviour is no longer observed, offering a plausible explanation as to the source of misconvergence in adaptive blind system identification. |
M R P Thomas Glottal-Synchronous Speech Processing PhD Thesis Imperial College London, 2010. @phdthesis{Thomas2010c,Glottal-synchronous speech processing is a field of speech science where the pseudoperiodicity of voiced speech is exploited. Traditionally, speech processing involves segmenting and processing short speech frames of predefined length; this may fail to exploit the inherent periodic structure of voiced speech which glottal-synchronous speech frames have the potential to harness. Glottal-synchronous frames are often derived from the glottal closure instants (GCIs) and glottal opening instants (GOIs). The SIGMA algorithm was developed for the detection of GCIs and GOIs from the Electroglottograph signal with a measured accuracy of up to 99.59%. For GCI and GOI detection from speech signals, the YAGA algorithm provides a measured accuracy of up to 99.84%. Multichannel speech-based approaches are shown to be more robust to reverberation than single-channel algorithms. The GCIs are applied to real-world applications including speech dereverberation, where SNR is improved by up to 5 dB, and to prosodic manipulation where the importance of voicing detection in glottal-synchronous algorithms is demonstrated by subjective testing. The GCIs are further exploited in a new area of data-driven speech modelling, providing new insights into speech production and a set of tools to aid deployment into real-world applications. The technique is shown to be applicable in areas of speech coding, identification and artificial bandwidth extension of telephone speech. |
M R P Thomas; B Geiser; J Gudnason; P A Naylor; P Vary Voice Source Estimation for Artificial Bandwidth Extension of Telephone Speech Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Dallas, TX, USA, 2010. @inproceedings{Thomas2010a,Artificial bandwidth extension (ABWE) of speech signals aims to estimate wideband speech (50 Hz – 7 kHz) from narrowband signals (300 Hz – 3.4 kHz). Applying the source-filter model of speech, many existing algorithms estimate vocal tract filter parameters independently of the source signal. However, many current methods for extending the narrowband voice source signal are limited to straightforward signal processing techniques which are only effective for high-band estimation. This paper presents a method for ABWE that employs novel data-driven modelling and an existing spectral mirroring technique to estimate the wideband source signal in both the high and low extension bands. A state-of-the-art Hidden Markov Model-based estimator evaluates the temporal and spectral envelopes in the missing frequency bands, with which the ABWE speech signal is synthesized. Informal listening tests comparing two existing source estimation techniques and two permutations of the proposed approach show an improvement in the perceived bandwidth of speech signals, in particular towards low frequencies. Subjective tests on the same data show a preference for the proposed techniques over the existing methods under test. |
N D Gaubitch; M R P Thomas; P A Naylor Dereverberation using LPC-based Approaches Book Section In: P A Naylor; N D Gaubitch (Ed.): Speech Dereverberation, pp. 99–132, Springer, 2010. @incollection{Gaubitch2010,A class of reverberant speech enhancement techniques involve processing of the linear prediction residual signal following Linear Predictive Coding (LPC). These approaches are based on the assumption that reverberation is mainly confined to the prediction residual and affects the LPC coefficients to a lesser extent. This Chapter begins with a study on the effects of reverberation on the LPC parameters where mathematical tools from statistical room acoustics are used in the analysis. Consequently, a general framework for dereverberation using LPC is formulated and several existing methods utilizing this approach are reviewed. Finally, a specific method for processing a reverberant prediction residual is presented in detail. This method uses a combination of spatial averaging and larynx cycle-based temporal averaging. Experiments with a microphone array in a small office demonstrate the dereverberation and noise suppression of the spatiotemporal averaging method, showing up to a 5 dB improvement in segmental SRR and 0.33 in normalized Bark spectral distortion score. |
2009 |
Jon Gudnason; Mark R P Thomas; Patrick A Naylor; Dan P W Ellis Proc. Interspeech Conf., Brighton, UK, 2009. @conference{Gudnason2009b,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. |
M R P Thomas; J Gudnason; P A Naylor Detection of Glottal Closing and Opening Instants Using the Improved DYPSA Framework Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Glasgow, Scotland, 2009. @inproceedings{Thomas2009c,Accurate estimation of glottal closure instants (GCIs) and opening instants (GOIs) is important for speech processing applications that benefit from glottal-synchronous processing. This paper proposes a novel improvement to the DYPSA framework, based upon a multiscale analysis technique and an accurate estimation of glottal volume velocity. This replaces the linear prediction residual for candidate selection and enables the reliable detection of both GCI and GOI candidates. A two-stage dynamic programming process then detects the GCIs and removes them from the candidate set, before detecting GOIs from the remaining candidates. A post-processing step improves GOI detection using the estimated GCIs. Evaluation against hand-labelled data on a large speech database shows that GCI detection is marginally improved compared with original DYPSA at 96% but, more importantly, shows that GOI detection can be achieved to a similar accuracy of 95%. |
M R P Thomas; J Gudnason; P A Naylor Data-Driven Voice Source Waveform Modelling Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, 2009. @inproceedings{Thomas2009a,This paper presents a data-driven approach to the modelling of voice source waveforms. The voice source is a signal that is estimated by inverse-filtering speech signals with an estimate of the vocal tract filter. It is used in speech analysis, synthesis, recognition and coding to decompose a speech signal into its source and vocal tract filter components. Existing approaches parameterize the voice source signal with physically- or mathematically-motivated models. Though the models 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 we present a data-driven approach to classify types of voice source waveforms based upon their melfrequency cepstrum coefficients with Gaussian mixture modelling. A set of “prototype” waveform classes is derived from a weighted average of voice source cycles from real data. An unknown speech signal is then decomposed into its prototype components and resynthesized. Results indicate that with sixteen voice source classes, low resynthesis errors can be achieved. |
M R P Thomas; P A Naylor The SIGMA Algorithm: A Glottal Activity Detector for Electroglottographic Signals Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 8, pp. 1557–1566, 2009. @article{Thomas2009b,Accurate estimation of glottal closure instants (GCIs) and opening instants (GOIs) is important for speech processing applications that benefit from glottal-synchronous processing. The majority of existing approaches detect GCIs by comparing the differentiated EGG signal to a threshold and are able to provide accurate results during voiced speech. More recent algorithms use a similar approach across multiple dyadic scales using the stationary wavelet transform. All existing approaches are however prone to errors around the transition regions at the end of voiced segments of speech. This paper describes a new method for EGG-based glottal activity detection which exhibits high accuracy over the entirety of voiced segments, including, in particular, the transition regions, thereby giving significant improvement over existing methods. Following a stationary wavelet transform-based preprocessor, detection of excitation due to glottal closure is performed using a group delay function and then true and false detections are discriminated by Gaussian mixture modeling. GOI detection involves additional processing using the estimated GCIs. The main purpose of our algorithm is to provide a ground-truth for GCIs and GOIs. This is essential in order to evaluate algorithms that estimate GCIs and GOIs from the speech signal only, and is also of high value in the analysis of pathological speech where knowledge of GCIs and GOIs is often needed. We compare our algorithm with two previous algorithms against a hand-labeled database. Evaluation has shown an average GCI hit rate of 99.47% and GOI of 99.35%, compared to 96.08 and 92.54 for the best-performing existing algorithm. |
2008 |
M R P Thomas; P A Naylor The SIGMA Algorithm for Estimation of Reference-Quality Glottal Closure Instants from Electroglottograph Signals Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Lausanne, Switzerland, 2008. @inproceedings{Thomas2008c,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. |
M R P Thomas; J Gudnason; P A Naylor Application of the DYPSA Algorithm to Segmented Time-Scale Modification of Speech Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Lausanne, Switzerland, 2008. @inproceedings{Thomas2008b,This paper presents a method for speech time scale modification. Voiced speech is pseudo-periodic, allowing time scale modification by the repetition or removal of cycles as necessary. However, in the case of unvoiced speech and at the boundaries of voiced speech, no such periodicity exists so the speech should not be modified. To address this issue, the proposed approach is novel in its use of the DYPSA algorithm to derive speech periodicity from glottal closure instants (GCIs), followed by a Gaussian Mixture model-based voiced/unvoiced/silence (VUS) classifier. A listening test based on ITU-T P800 has been conducted and has shown that, by employing VUS detection, the average mean opinion score of the perceptual quality of processed speech exceeds that of a method without VUS detection by 0.61 over a range of modification factors. Results are presented as a function of modification factor for normal and fast original talking rate. Reliable time scale modification of high audio quality enables many applications, such as time scale compression for fast scanning of recorded voicemail messages, slowing talking rate for improved intelligibility in forensics and lip synchronization in motion video. |
2007 |
M R P Thomas; N D Gaubitch; J Gudnason; P A Naylor A Practical Multichannel Dereverberation Algorithm Using Multichannel DYPSA and Spatiotemporal Averaging Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, 2007. @inproceedings{Thomas2007b,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. |
N D Gaubitch; M R P Thomas; P A Naylor Subband Method for Multichannel Least Squares Equalization of Room Transfer Functions Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, 2007. @inproceedings{Gaubitch2007a,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. |
M R P Thomas; N D Gaubitch; P A Naylor Multichannel DYPSA for estimation of glottal closure instants in reverberant speech Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Poznan, Poland, 2007. @inproceedings{Thomas2007a,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. |
2006 |
M R P Thomas A Novel Loudspeaker Equalizer Masters Thesis Imperial College London, 2006. @mastersthesis{Thomas2006,Fundamentally, loudspeaker design has changed very little in the past 30 years. The late 70s saw the introduction of electromechanical modelling techniques which remain the basis for the design and analysis of loudspeakers today. Aside from the use of lighter, stronger materials in the construction of drive units, the area which has undergone the most development is the design of equalisers. Classically, loudspeakers use a passive analogue filter network to compensate for a non-flat frequency response, but they are far from ideal and are prone to variation with temperature and age. Recent years have seen the use of linear DSP equalisers which conform to much tighter specifications. However, there are two major flaws in the design of even the latest equalisers. Firstly, it has long been known that at extreme voice coil excursion a loudspeaker is a nonlinear device, though no documented attempt at producing a nonlinear equaliser has yet been proposed. Secondly is the use of swept sine tones to characterise frequency responses, which can sometimes yield different results to methods where excitation energy is spread over a wider bandwidth (which is more akin to music or speech). Swept sines generally provide no phase information, which is an area of increasing interest in loudspeaker equalisation. This project investigates the analysis of loudspeaker frequency responses using a Maximum-Length Sequence (MLS) or M-Sequence Decorrelation technique, which uses pseudorandom noise to yield both amplitude and phase information. The measurements are used to model the frequency response over a wide range of amplitudes, fitting a Volterra-Series approximation and defining a level- dependent equaliser. |
Publications
2012 |
Detection of Glottal Closing Instants from Voiced Speech: A Quantitative Review Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 20, no. 3, pp. 994–1006, 2012. |
Inference of Room Geometry from Acoustic Impulse Responses Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., 2012. |
Estimation of Glottal Closing and Opening Instants in Voiced Speech using the YAGA Algorithm Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 20, no. 1, pp. 82–91, 2012. |
2011 |
Exact Localization of Acoustic Reflectors from Quadratic Constraints Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, 2011. |
Application of Channel Shortening to Acoustic Channel Equalization in the Presence of Noise and Estimation Error Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, USA, 2011. |
The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensing and Rendering Proceedings Article In: Proc. Audio Eng. Soc. Convention, New York, 2011. |
Simulating Room Impulse Responses for Spherical Microphone Arrays Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2011. |
Robust Inference of Room Geometry from Acoustic Impulse Responses Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Barcelona, Spain, 2011. |
Data-Driven Voice Source Waveform Analysis and Synthesis Journal Article In: Speech Communication, vol. 54, no. 2, pp. 199–211, 2011. |
Dereverberation Performance of Rigid and Open Spherical Microphone Arrays: Theory & Simulation Proceedings Article In: Proc. Joint Workshop on Hands-Free Speech Communication and Microphone Arrays (HSCMA), Edinburgh, UK, 2011. |
2010 |
Supervised Identification and Removal of Common Filter Components in Adaptive Blind SIMO System Identification Proceedings Article In: Proc. Intl. Workshop Acoust. Echo Noise Control (IWAENC), Tel Aviv, Israel, 2010. |
Glottal-Synchronous Speech Processing PhD Thesis Imperial College London, 2010. |
Voice Source Estimation for Artificial Bandwidth Extension of Telephone Speech Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Dallas, TX, USA, 2010. |
Dereverberation using LPC-based Approaches Book Section In: P A Naylor; N D Gaubitch (Ed.): Speech Dereverberation, pp. 99–132, Springer, 2010. |
2009 |
Proc. Interspeech Conf., Brighton, UK, 2009. |
Detection of Glottal Closing and Opening Instants Using the Improved DYPSA Framework Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Glasgow, Scotland, 2009. |
Data-Driven Voice Source Waveform Modelling Proceedings Article In: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, 2009. |
The SIGMA Algorithm: A Glottal Activity Detector for Electroglottographic Signals Journal Article In: IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 8, pp. 1557–1566, 2009. |
2008 |
The SIGMA Algorithm for Estimation of Reference-Quality Glottal Closure Instants from Electroglottograph Signals Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Lausanne, Switzerland, 2008. |
Application of the DYPSA Algorithm to Segmented Time-Scale Modification of Speech Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Lausanne, Switzerland, 2008. |
2007 |
A Practical Multichannel Dereverberation Algorithm Using Multichannel DYPSA and Spatiotemporal Averaging Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, 2007. |
Subband Method for Multichannel Least Squares Equalization of Room Transfer Functions Proceedings Article In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, 2007. |
Multichannel DYPSA for estimation of glottal closure instants in reverberant speech Proceedings Article In: Proc. European Signal Processing Conf. (EUSIPCO), Poznan, Poland, 2007. |
2006 |
A Novel Loudspeaker Equalizer Masters Thesis Imperial College London, 2006. |