Publications
443 results found
Cauchi B, Javed H, Gerkmann T, et al., 2016, PERCEPTUAL AND INSTRUMENTAL EVALUATION OF THE PERCEIVED LEVEL OF REVERBERATION, 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 629-633, ISSN: 1520-6149
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- Citations: 6
Javed HA, Moore AH, Naylor PA, 2016, SPHERICAL HARMONIC RAKE RECEIVERS FOR DEREVERBERATION, 15th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE
Hu M, Sharma D, Doclo S, et al., 2016, Blind adaptive SIMO acoustic system identification using a locally optimal step-size, 60th AES International Conference on Dereverberation and Reverberation of Audio, Music, and Speech (DREAMS), Publisher: AUDIO ENGINEERING SOC INC
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- Citations: 2
Cauchi B, Gerkmann T, Doclo S, et al., 2016, Spectrally and spatially informed noise suppression using beamforming and convolutive NMF, 60th AES International Conference on Dereverberation and Reverberation of Audio, Music, and Speech (DREAMS), Publisher: AUDIO ENGINEERING SOC INC
Antonello N, De Sena E, Moonen M, et al., 2016, Sound field control in a reverberant room using the Finite Difference Time Domain method, 60th AES International Conference on Dereverberation and Reverberation of Audio, Music, and Speech (DREAMS), Publisher: AUDIO ENGINEERING SOC INC
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- Citations: 1
Parada PP, Sharma D, Naylor PA, et al., 2016, Analysis of prediction intervals for non-intrusive estimation of speech clarity index, 60th AES International Conference on Dereverberation and Reverberation of Audio, Music, and Speech (DREAMS), Publisher: AUDIO ENGINEERING SOC INC
Zhang W, Naylor PA, He Z, et al., 2016, ON THE EVALUATION OF MULTICHANNEL BLIND SYSTEM IDENTIFICATION FROM THE VIEWPOINT OF SYSTEM EQUALIZATION, 15th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE
Zhang W, Naylor PA, 2016, AN ITERATIVE METHOD FOR EQUALIZATION OF MULTICHANNEL ACOUSTIC SYSTEMS ROBUST TO SYSTEM IDENTIFICATION ERRORS, 15th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE
De Sena E, Kaplanis N, Naylor PA, et al., 2016, Large-scale auralised sound localisation experiment, 60th AES International Conference on Dereverberation and Reverberation of Audio, Music, and Speech (DREAMS), Publisher: AUDIO ENGINEERING SOC INC
Manning V, Yiallourides C, Brevadt M, et al., 2015, Knee sounds may predict osteoarthritis severity, symptoms and function: pilot investigation toward a novel dynamic imaging system, Arthritis & Rheumatology, Vol: 67, ISSN: 2326-5191
Eaton J, Gaubitch ND, Moore AH, et al., 2015, Proceedings of the ACE Challenge Workshop, a satellite event of IEEE-WASPAA
Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room. Recently, several important methods in speech enhancement and speech recognition have been developed that show an increase in performance compared to the predecessors but do require knowledge of one or more fundamental acoustical parameters such as the T60. Traditionally, these parameters have been estimated using carefully measured Acoustic Impulse Responses (AIRs). However, in most applications it is not practical or even possible to measure the acoustic impulse response. Consequently, there is increasing research activity in the estimation of such parameters directly from speech and audio signals. The aim of this challenge was to evaluate state-of-the-art algorithms for blind acoustic parameter estimation from speech and to promote the emerging area of research in this field. Participants evaluated their algorithms for T60 and DRR estimation against the ’ground truth’ values provided with the data-sets and presented the results in a paper describing the method used.
Eaton J, Naylor PA, 2015, Direct-to-Reverberant ratio estimation on the ACE corpus using a Two-channel beamformer, arXiv, ACE Challenge Workshop, a satellite event of IEEE-WASPAA, Publisher: arXiv
Direct-to-Reverberant Ratio (DRR) is an important measure for characterizing the properties of a room. The recently proposed DRR Estimation using a Null-Steered Beamformer (DENBE) algorithm was originally tested on simulated data where noise was artificially added to the speech after convolution with impulse responses simulated using the image-source method. This paper evaluates the performance of this algorithm on speech convolved with measured impulse responses and noise using the Acoustic Characterization of Environments (ACE) Evaluation corpus. The fullband DRR estimation performance of the DENBE algorithm exceeds that of the baselines in all Signal-to-Noise Ratios (SNRs) and noise types. In addition, estimation of the DRR in one third-octave ISO frequency bands is demonstrated.
Eaton J, Gaubitch ND, Moore AH, et al., 2015, The ACE Challenge - corpus description and performance evaluation, WASPAA, Publisher: IEEE
Knowledge of the Direct-to-Reverberant Ratio (DRR) and Reverberation Time (T60) can be used to better perform speech and audio processing such as dereverberation. Established methods compute these parameters from measured Acoustic Impulse Responses (AIRs). However, in many practical situations the AIR is not available and the parameters must be estimated non-intrusively directly from noisy speech or audio signals. The Acoustic Characterization of Environments (ACE) Challenge is a competition to identify the most promising non-intrusive DRR and T60 estimation methods using real noisy reverberant speech. We describe the ACE corpus comprising multi-channel AIRs, and multi-channel noise including ambient, fan and babble noise recorded in the same environment as the measured AIRs, along with the corresponding DRR and T60 measurements. The evaluation methodology is discussed and comparative results are shown.
Eaton J, Naylor PA, 2015, Reverberation time estimation on the ACE corpus using the SDD method, arXiv, ACE Challenge Workshop, a satellite event of IEEE-WASPAA, Publisher: arXiv
Reverberation Time ($T_60$) is an important measure for characterizing the properties of a room. The author’s $T_60$ estimation algorithm was previously tested on simulated data where the noise is artificially added to the speech after convolution with a impulse responses simulated using the image method. We test the algorithm on speech convolved with real recorded impulse responses and noise from the same rooms from the Acoustic Characterization of Environments (ACE) corpus and achieve results comparable results to those using simulated data.
Doire C, Brookes D, Naylor P, et al., 2015, Data-Driven Statistical Modelling of Room Impulse Responses in the Power Domain, European Signal Processing Conference (EUSIPCO), Publisher: IEEE
Having an accurate statistical model of room impulse responses with a minimum number of parameters is of crucial importance in applications such as dereverberation. In this paper, by taking into account the behaviour of the early reflections, we extend the widely-used statistical model proposed by Polack. The squared room impulse response is modelled in each frequency band as the realisation of a stochastic process weighted by the sum of two exponential decays. Room-independent values for the new parameters involved are obtained through analysis of several room impulse response databases, and validation of the model in the likelihood sense is performed.
Hu M, Doclo S, Sharma D, et al., 2015, Noise Robust Blind System Identification Algorithms Based On A Rayleigh Quotient Cost Function, European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 2476-2480
An important prerequisite for acoustic multi-channel equalization for speech dereverberation involves the identification of the acoustic channels between the source and the microphones. Blind System Identification (BSI) algorithms based on cross-relation error minimization are known to mis-converge in the presence of noise. Although algorithms have been proposed in the literature to improve robustness to noise, the estimated room impulse responses are usually constrained to have a flat magnitude spectrum. In this paper, noise robust algorithms based on a Rayleigh quotient cost function are proposed. Unlike the traditional algorithms, the estimated impulse responses are not always forced to have unit norm. Experimental results using simulated room impulse responses and several SNRs show that one of the proposed algorithms outperforms competing algorithms in terms of normalized projection misalignment.
Moore AH, Evers C, Naylor PA, et al., 2015, Direction of arrival estimation using pseudo-intensity vectors with direct-path dominance test, European Signal Processing Conference, Publisher: IEEE, Pages: 2296-2300, ISSN: 2219-5491
The accuracy of direction of arrival estimation tends to degrade under reverberant conditions due to the presence of reflected signal components which are correlated with the direct path. The recently proposed direct-path dominance test provides a means of identifying time-frequency regions in which a single signal path is dominant. By analysing only these regions it was shown that the accuracy of the FS-MUSIC algorithm could be significantly improved. However, for real-time implementation a less computationally demanding localisation algorithm would be preferable. In the present contribution we investigate the direct-path dominance test as a preprocessing step to pseudo-intensity vector-based localisation. A novel formulation of the pseudo-intensity vector is proposed which further exploits the direct path dominance test and leads to improved localisation performance.
Evers C, Moore AH, Naylor PA, et al., 2015, Bearing-only acoustic tracking of moving speakers for robot audition, 2015 IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, Pages: 1206-1210, ISSN: 1546-1874
This paper focuses on speaker tracking in robot audition for human-robot interaction. Using only acoustic signals, speaker tracking in enclosed spaces is subject to missing detections and spurious clutter measurements due to speech inactivity, reverberation and interference. Furthermore, many acoustic localization approaches estimate speaker direction, hence providing bearing-only measurements without range information. This paper presents a probability hypothesis density (PHD) tracker that augments the bearing-only speaker directions of arrival with a cloud of range hypotheses at speaker initiation and propagates the random variates through time. Furthermore, due to their formulation PHD filters explicitly model, and hence provide robustness against, clutter and missing detections. The approach is verified using experimental results.
Moore AH, Evers C, Naylor PA, 2015, Multichannel equalisation for high-order spherical microphone arrays using beamformed channels, 2015 IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, Pages: 1211-1215, ISSN: 1546-1874
High-order spherical microphone arrays offer many practical benefits including relatively fine spatial resolution in all directions and rotation invariant processing using eigenbeams. Spatial filtering can reduce interference from noise and reverberation but in even moderately reverberant environments the beam pattern fails to suppress reverberation to a level adequate for typical applications. In this paper we investigate the feasibility of applying dereverberation by considering multiple beamformer outputs as channels to be dereverberated. In one realisation we process directly in the spherical harmonic domain where the beampatterns are mutually orthogonal. In a second realisation, which is not limited to spherical microphone arrays, beams are pointed in the direction of dominant reflections. Simulations demonstrate that in both cases reverberation is significantly reduced and, in the best case, clarity index is improved by 15 dB.
Parada PP, Sharma D, Naylor PA, et al., 2015, Reverberant speech recognition exploiting clarity index estimation, Eurasip Journal on Advances in Signal Processing, Vol: 2016, Pages: 1-12, ISSN: 1687-6180
We present single-channel approaches to robust automatic speech recognition (ASR) in reverberant environments based on non-intrusive estimation of the clarity index (C 50). Our best performing method includes the estimated value of C 50 in the ASR feature vector and also uses C 50 to select the most suitable ASR acoustic model according to the reverberation level. We evaluate our method on the REVERB Challenge database employing two different C 50 estimators and show that our method outperforms the best baseline of the challenge achieved without unsupervised acoustic model adaptation, i.e. using multi-condition hidden Markov models (HMMs). Our approach achieves a 22.4 % relative word error rate reduction in comparison to the best baseline of the challenge.
Eaton J, Moore AH, Naylor PA, et al., 2015, Direct-to-reverberant ratio estimation using a null-steered beamformer, ICASSP, Publisher: IEEE, Pages: 46-50
Reverberation affects the quality and intelligibility of distant speech recorded in a room. Direct-to-Reverberant Ratio (DRR) is a useful measure for assessing the acoustic configuration and can be used to inform dereverberation algorithms. We describe a novel DRR estimation algorithm applicable where the signal was recorded with two or more microphones, such as mobile communications devices and laptops. The method uses a null-steered beamformer. In simulations the proposed method yields accurate DRR estimates to within +/- 4 dB across a across a wide variety of room sizes, reverberation times and source-receiver distances. It is also shown that the proposed method is more robust to background noise than a baseline approach. The best estimation accuracy is obtained in the region from -5 to 5 dB which is a relevant range for portable devices.
Zahedi A, Ostergaard J, Jensen SH, et al., 2015, Audio coding in wireless acoustic sensor networks, SIGNAL PROCESSING, Vol: 107, Pages: 141-152, ISSN: 0165-1684
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- Citations: 11
Hu M, sharma D, Doclo S, et al., 2015, Speaker change detection and speaker diarization using spatial information, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Antonello N, van Waterschoot T, Moonen M, et 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.
Doire 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
Zahedi A, Ostergaard J, Jensen SH, et al., 2015, Coding and Enhancement in Wireless Acoustic Sensor Networks, Data Compression Conference (DCC), Publisher: IEEE, Pages: 293-302, ISSN: 1068-0314
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- Citations: 4
Hu M, Sharma D, Doclo S, et al., 2015, SPEAKER CHANGE DETECTION AND SPEAKER DIARIZATION USING SPATIAL INFORMATION, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 5743-5747, ISSN: 1520-6149
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- Citations: 6
Eaton J, Moore AH, Naylor PA, et al., 2015, DIRECT-TO-REVERBERANT RATIO ESTIMATION USING A NULL-STEERED BEAMFORMER, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 46-50, ISSN: 1520-6149
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- Citations: 13
Doire 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
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- Citations: 2
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
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- Citations: 1
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