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Journal articleSharma D, Naylor PA, Wang Y, et al., 2016,
A Data-Driven Non-intrusive Measure of Speech Quality and Intelligibility
, Speech Communication, Vol: 80, Pages: 84-94, ISSN: 0167-6393Speech signals are often affected by additive noiseand distortion which can degrade the perceived quality andintelligibility of the signal. We present a new measure, NISA, forestimating the quality and intelligibility of speech degraded byadditive noise and distortions associated with telecommunicationsnetworks, based on a data driven framework of feature extractionand tree based regression. The new measure is non-intrusive,operating on the degraded signal alone without the need for areference signal. This makes the measure applicable to practicalspeech processing applications operating in the single-endedmode. The new measure has been evaluated against the intrusivemeasures PESQ and STOI. The results indicate that the accuracyof the new non-intrusive method is around 90% of the accuracy ofthe intrusive measures, depending on the test scenario. The NISAmeasure therefore provides non-intrusive (single-ended) PESQand STOI estimates with high accuracy.
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Conference paperJaved HA, Moore AH, Naylor PA, 2016,
Spherical microphone array acoustic rake receivers
, ICASSP, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 111-115, ISSN: 0736-7791Several signal independent acoustic rake receivers are proposed for speech dereverberation using spherical microphone arrays. The proposed rake designs take advantage of multipaths, by separately capturing and combining early reflections with the direct path. We investigate several approaches in combining reflections with the direct path source signal, including the development of beam patterns that point nulls at all preceding reflections. The proposed designs are tested in experimental simulations and their dereverberation performances evaluated using objective measures. For the tested configuration, the proposed designs achieve higher levels of dereverberation compared to conventional signal independent beamforming systems; achieving up to 3.6 dB improvement in the direct-to-reverberant ratio over the plane-wave decomposition beamformer.
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Conference paperEvers C, Moore AH, Naylor PA, 2016,
Acoustic simultaneous localization and mapping (A-SLAM) of a moving microphone array and its surrounding speakers
, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 6-10, ISSN: 1520-6149Acoustic scene mapping creates a representation of positions of audio sources such as talkers within the surrounding environment of a microphone array. By allowing the array to move, the acoustic scene can be explored in order to improve the map. Furthermore, the spatial diversity of the kinematic array allows for estimation of the source-sensor distance in scenarios where source directions of arrival are measured. As sound source localization is performed relative to the array position, mapping of acoustic sources requires knowledge of the absolute position of the microphone array in the room. If the array is moving, its absolute position is unknown in practice. Hence, Simultaneous Localization and Mapping (SLAM) is required in order to localize the microphone array position and map the surrounding sound sources. In realistic environments, microphone arrays receive a convolutive mixture of direct-path speech signals, noise and reflections due to reverberation. A key challenge of Acoustic SLAM (a-SLAM) is robustness against reverberant clutter measurements and missing source detections. This paper proposes a novel bearing-only a-SLAM approach using a Single-Cluster Probability Hypothesis Density filter. Results demonstrate convergence to accurate estimates of the array trajectory and source positions.
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Journal articleNeeld T, Eaton J, Naylor PA, et al., 2016,
A novel method of determining events in combination gas boilers: Assessing the feasibility of a passive acoustic sensor
, Building and Environment, Vol: 100, Pages: 1-9, ISSN: 0360-1323To assess the impact of interventions designed to reduce residential space heating demand, investigators must be armed with field-trial applicable techniques that accurately measure space heating energy use. This study assesses the feasibility of using a passive acoustic sensor to detect gas consumption events in domestic combination gas-fired boilers (C-GFBs). The investigation has shown, for the C-GFB investigated, the following events are discernible using a passive acoustic sensor: demand type (hot water or central heating); boiler ignition time; and pre-mix fan motor speed. A detection algorithm was developed to automatically identify demand type and burner ignition time with accuracies of 100% and 97% respectfully. Demand type was determined by training a naive Bayes classifier on 20 features of the acoustic profile at the start of a demand event. Burner ignition was determined by detecting low frequency (5–10 Hz) pressure pulsations produced during ignition. The acoustic signatures of the pre-mix fan and circulation-pump were identified manually. Additional work is required to detect burner duration, deal with detection in the presence of increased noise and expand the range of boilers investigated. There are considerable implications resulting from the widespread use of such techniques on improving understanding of space heating demand.
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Conference paperDoire CSJ, Brookes DM, Naylor PA, et al., 2016,
Acoustic Environment Control: Implementation of a Reverberation Enhancement System
, AES 60th International Conference: DREAMS (Dereverberation and Reverberation of Audio, Music, and Speech)Reverberation enhancement systems allow the active control of the acoustic environment. They are subject to instability issues due to acoustic feedback, and are often installed permanently in large halls, sometimes at great cost. In this paper, we explore the possibility of implementing a cost-effective reverberation enhancement system to control the acoustics of typical rooms using a combination of spatial filtering, automatic calibration, adaptive notch filters, howling detection and manual adjustments. The effectiveness of the system is then tested inside a small soundproof booth.
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Journal articleParada PP, Sharma D, Lainez J, et al., 2016,
A single-channel non-intrusive C50 estimator correlated with speech recognition performance
, IEEE/ACM Transactions on Audio, Speech and Language Processing, Vol: 24, Pages: 719-732, ISSN: 2329-9304 -
Conference paperEvers C, Moore A, Naylor P, 2016,
Towards Informative Path Planning for Acoustic SLAM
, DAGA 2016Acoustic scene mapping is a challenging task as microphonearrays can often localize sound sources only interms of their directions. Spatial diversity can be exploitedconstructively to infer source-sensor range whenusing microphone arrays installed on moving platforms,such as robots. As the absolute location of a moving robotis often unknown in practice, Acoustic SimultaneousLocalization And Mapping (a-SLAM) is required in orderto localize the moving robot’s positions and jointlymap the sound sources. Using a novel a-SLAM approach,this paper investigates the impact of the choice of robotpaths on source mapping accuracy. Simulation results demonstratethat a-SLAM performance can be improved byinformatively planning robot paths.
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Conference paperCauchi B, Santos JF, Siedenburg K, et al., 2016,
Predicting the quality of processed speech by combining modulation-based features and model trees
, Pages: 180-184Many signal processing methods have been proposed to improve the quality of speech recorded in the presence of noise and reverberation. The evaluation of these methods either requires the use of perceptual measures, i.e. listening tests, or instrumental measures. Perceptual measures are typically more reliable but are quite costly and time-consuming. On the other hand, instrumental measures may correlate poorly with the perceived speech quality. In this paper we propose to train an instrumental measure, combining modulation-based features and model trees, on the basis of perceptual scores obtained on a small corpus of speech data that has been processed by a combination of beamforming and spectral postfiltering. For evaluation purposes the resulting measure is then applied to a larger corpus. Results show that the use of model trees to train the predicting function of an instrumental measure increases its correlation with perceptual scores.
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Conference paperHafezi S, Moore AH, Naylor PA, 2016,
3D ACOUSTIC SOURCE LOCALIZATION IN THE SPHERICAL HARMONIC DOMAIN BASED ON OPTIMIZED GRID SEARCH
, 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 415-419, ISSN: 1520-6149- Author Web Link
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- Citations: 11
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Conference paperZahedi A, Ostergaard J, Jensen SH, et al., 2016,
On Perceptual Audio Compression with Side Information at the Decoder
, Data Compression Conference (DCC), Publisher: IEEE, Pages: 456-465, ISSN: 1068-0314 -
Conference paperCauchi 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- Author Web Link
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- Citations: 6
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Conference paperJaved HA, Moore AH, Naylor PA, 2016,
SPHERICAL HARMONIC RAKE RECEIVERS FOR DEREVERBERATION
, 15th International Workshop on Acoustic Signal Enhancement (IWAENC), Publisher: IEEE -
Conference paperHu 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- Author Web Link
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- Citations: 2
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Conference paperCauchi 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 -
Conference paperAntonello 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- Author Web Link
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- Citations: 1
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Conference paperParada 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 -
Conference paperZhang 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 -
Conference paperZhang 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 -
Conference paperDe 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 -
Conference paperEaton 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: arXivDirect-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.
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