331 results found
Gaubitch ND, Löllmann HW, Jeub M, et al., 2012, Performance comparison of algorithms for blind reverberation time estimation from speech
© 2012, Institute of Electrical and Electronics Engineers Inc. All rights reserved. The reverberation time, T60, is one of the key parameters used to quantify room acoustics. It can provide information about the quality and intelligibility of speech recorded in a reverberant environment, and it can be used to increase robustness to reverberation of speech processing algorithms. T60 can be determined directly from a measurement of the acoustic impulse response, but in situations where this is unavailable it must be estimated blindly from reverberant speech. In this contribution, we provide a study of three state-of-the-art methods for blind T60 estimation. Experimental results with a large number of talkers, simulated and measured acoustic impulse responses, and various levels of additive white Gaussian noise are presented. The relative merits of the three methods in terms of computational time, estimation accuracy, noise sensitivity and inter-talker variance are discussed. In general, all three methods are able to estimate the reverberation time to within 0.2 s for T60 ≤ 0.8 s and SNR ≥ 30 dB, while increasing the noise level causes overestimation. The relative computational speed of the three methods is also assessed.
Naylor PA, Gaubitch ND, 2012, Acoustic signal processing in noise: It's not getting any quieter
© 2012, Institute of Electrical and Electronics Engineers Inc. All rights reserved. Acoustic signal processing research has been addressing the issues associated with additive noise and other degradations in speech for many years and several significant technical advances are now embedded in the state-of-the-art. Nevertheless, the problems are not solved and may actually be worsening. The philosophy advocated in this paper is that further improvements in acoustic signal processing for noise reduction and robustness are, of course, important but are unlikely to be sufficient on their own. Alongside the signal processing, successful systems are likely going to need to include two further factors: an element of matching to the human perception system and also an element of sensing and adaptation to the local environment, giving systems acoustic awareness. Examples of current research on human perception and acoustic signal processing are discussed. These include some aspects of auditory cognition and signal processing methods for building acoustic awareness. A new initiative for benchmarking is also highlighted.
Jarrett D, Habets EAP, Thomas M, et al., 2012, Rigid sphere room impulse response simulation: algorithm and applications, J. Acoust. Soc. America, Vol: 132
Annibale P, Filos J, Naylor PA, et al., 2012, TDOA-based speed of sound estimation for air temperature and room geometry inference, IEEE Trans. Audio, Speech, Lang. Process.
Antonacci F, Filos J, Thomas M, et al., 2012, Inference of room geometry from acoustic impulse responses, IEEE Trans. Audio Speech Language Proc., Vol: 20, Pages: 2683-2695
Annibale P, Antonacci F, Bestagini P, et al., 2011, The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensing and Rendering
Slaney M, Naylor PA, 2011, Audio and Acoustic Signal Processing, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 28, Pages: 160-U26, ISSN: 1053-5888
Loganathan P, Habets EAP, Naylor PA, 2011, A Proportionate Adaptive Algorithm with Variable Partitioned Block Length for Acoustic Echo Cancellation
Jarrett DP, Thomas MR, Habets EAP, et al., 2011, Simulating Room Impulse Responses for Spherical Microphone Arrays
Sharma D, Hilkhuysen G, Gaubitch ND, et al., 2011, C-Qual - A validation of PESQ using degradations encountered in forensic and law enforcement audio, Pages: 177-181
Assessment of speech quality of law-enforcement audio recordings is important as degradations introduced by non-ideal recording conditions can reduce the intelligence value of such recordings. Furthermore a model that predicts speech quality could be beneficial for assessing the performance of audio collection and enhancement systems. The Perceptual Evaluation of Speech Quality (PESQ) algorithm (ITU-T P.862) has been validated for degradations common in telecommunications. In this paper we apply PESQ to degradations typically encountered in law-enforcement. Also we present a subjectively labeled database (C-Qual) containing distortions encountered in law enforcement scenarios. Comparing the prediction by PESQ and the observed opinions provided by the listeners shows that PESQ is less suitable for estimating the speech quality in this context.
Gaubitch ND, Brookes M, Naylor PA, et al., 2011, Bayesian Adaptive method for estimating Speech Intelligibility in noise, Pages: 169-174
We present the Bayesian Adaptive Speech Intelligibility Estimation (BASIE) method - a tool for rapid estimation of a given speech reception threshold (SRT) and the slope at that threshold of multiple psychometric functions for speech intelligibility in noise. The core of this tool is an adaptive Bayesian procedure, which adjusts the signal-to-noise ratio at each subsequent stimulus such that the expected variance of the threshold and slope estimates are minimised. Simulation results show that the algorithm is able to achieve SRT estimates accurate to within ±1 dB in under 30 iterations. Furthermore, we discuss strategies for using BASIE to evaluate the effects of speech processing algorithms on intelligibility and we give two illustrative examples for different noise reduction methods with supporting listening experiments.
Annibale P, Antonacci F, Bestagini P, et al., 2011, The SCENIC Project: Environment-aware Sound Sensing and Rendering, PROCEEDINGS OF THE 2ND EUROPEAN FUTURE TECHNOLOGIES CONFERENCE AND EXHIBITION 2011 (FET 11), Vol: 7, Pages: 150-152, ISSN: 1877-0509
Loganathan P, Habets EAP, Naylor PA, 2011, A PROPORTIONATE ADAPTIVE ALGORITHM WITH VARIABLE PARTITIONED BLOCK LENGTH FOR ACOUSTIC ECHO CANCELLATION, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 73-76, ISSN: 1520-6149
Sharma D, Naylor PA, Gaubitch ND, et al., 2011, Short-Time Objective Assessment of Speech Quality
Jarrett DP, Habets EAP, Thomas MRP, et al., 2011, Dereverberation performance of rigid and open spherical microphone arrays: theory & simulation
Thomas MRP, Gaubitch N, Naylor PA, 2011, Application of Channel Shortening to Acoustic Channel Equalization in the Presence of Noise and Estimation Error
Thomas MRP, Gudnason J, Naylor PA, 2011, Estimation of Glottal Closing and Opening Instants in Voiced Speech using the YAGA Algorithm, IEEE Trans. Audio Speech Language Proc., Vol: to appear
Canclini A, Antonacci F, Thomas MRP, et al., 2011, Exact Localization of Acoustic Reflectors from Quadratic Constraints
Filos J, Canclini A, Thomas MRP, et al., 2011, Robust Inference of Room Geometry From Acoustic Measurements Using the Hough Transform
Habets EAP, Benesty J, Naylor PA, 2011, A Cross-Relation Based Affine Projection Algorithm for Blind SIMO System Identification
Gudnason J, Thomas MRP, Ellis DPW, et al., 2011, Data-Driven Voice Source Waveform Analysis and Synthesis, Speech Communication, Vol: to appear
Gaubitch ND, Brookes M, Naylor PA, et al., 2011, Single-Microphone Blind Channel Identification in Speech Using Spectrum Classification
Rashobh R, Khong AWH, Naylor PA, 2010, Adaptive blind system identification for speech dereverberation using a priori estimates
Loganathan P, Habets EAP, Naylor PA, 2010, A Partitioned Block Proportionate Adaptive Algorithm for Acoustic Echo Cancellation
Nakatani T, Kellermann W, Naylor P, et al., 2010, Introduction to the Special Issue on Processing Reverberant Speech: Methodologies and Applications, IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, Vol: 18, Pages: 1673-1675, ISSN: 1558-7916
Tsakiris MC, Lopes CG, Naylor PA, 2010, An Alternative Criterion for Regularization in Recursive Least-Squares Problems, York, UK
Jarrett DP, Habets EAP, Naylor PA, 2010, Source Localization in the Spherical Harmonic Domain Using a Pseudointensity Vector
Jarrett DP, Habets EAP, Naylor PA, 2010, 3D Source Localization in the Spherical Harmonic Domain Using a Pseudointensity Vector, Aalborg, Denmark
Naylor PA, Gaubitch ND, 2010, Speech Dereverberation, Publisher: Springer, ISBN: 978-1-84996-056-4
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