Advanced Binaural Sound Localization in 3-D for Humanoid Robots

Keyrouz, Fakheredine

doi:10.1109/tim.2014.2308051

Cited by 47 publications

(24 citation statements)

References 22 publications

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“…SBL beamforming assumes a predefined spatial mapping between the sources and the sensors to infer the DOAs directly from the reconstructed source vector, as opposed to methods (including SBL-based 7 ) which infer the DOA of a single target talker indirectly through the estimation of the relative transfer function between a pair of microphones. 4,6 It is demonstrated both with simulations and experimental data that SBL beamforming offers unambiguous source localization outperforming traditional beamforming methods especially for correlated signals and single-snapshot measurements. The high-resolution SBL reconstruction offers not only speech enhancement over noise, but also speech separation between competing talkers.…”

mentioning

confidence: 97%

Sound source localization and speech enhancement with sparse Bayesian learning beamforming

Xenaki

Boldt

Christensen

2018

The Journal of the Acoustical Society of America

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Speech localization and enhancement involves sound source mapping and reconstruction from noisy recordings of speech mixtures with microphone arrays. Conventional beamforming methods suffer from low resolution, especially with a limited number of microphones. In practice, there are only a few sources compared to the possible directions-of-arrival (DOA). Hence, DOA estimation is formulated as a sparse signal reconstruction problem and solved with sparse Bayesian learning (SBL). SBL uses a hierarchical two-level Bayesian inference to reconstruct sparse estimates from a small set of observations. The first level derives the posterior probability of the complex source amplitudes from the data likelihood and the prior. The second level tunes the prior towards sparse solutions with hyperparameters which maximize the evidence, i.e., the data probability. The adaptive learning of the hyperparameters from the data auto-regularizes the inference problem towards sparse robust estimates. Simulations and experimental data demonstrate that SBL beamforming provides high-resolution DOA maps outperforming traditional methods especially for correlated or non-stationary signals. Specifically for speech signals, the high-resolution SBL reconstruction offers not only speech enhancement but effectively speech separation.

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confidence: 97%

Sound source localization and speech enhancement with sparse Bayesian learning beamforming

Xenaki

Boldt

Christensen

2018

The Journal of the Acoustical Society of America

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“…Some of these issues and applications have been focused in the last ten years, such as: modeling the localization of sounds in the azimuthal half-plane (Raspaud et al, 2010;Willert et al, 2006); sound localization in the presence of noise and reverberation (Devore et al, 2009;May et al, 2012;Woodruff and Wang, 2012;; robotic sound source localization (Keyrouz, 2014;Liu and Meng, 2008). However, most approaches up to now are based on experimental cochleagrams or head related transfer functions (HRTF) whose determination demands the use of an anechoic chamber and the introduction of microphones inside the listener's eardrum, besides other procedure constraints.…”

Section: Discussionmentioning

confidence: 99%

Psychoacoustic behavior of human listeners in lateralization judgments of binaural stimuli

2017

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Introduction: The present work aims to develop statistical models for the psychoacoustic behavior of human beings in lateralization judgments of binaural acoustic stimuli, as a function of Interaural Time Delay (ITD) and Interaural Amplitude Difference (IAD) for several Sensation Levels (SL). Such models intend to contribute to a deep comprehension of the perception or recognition mechanism which permits listeners to decide whether a source of a sound is located on the right or on the left side of their medial plane. Methods: Numerous lateralization judgments are accomplished through a computer controlled experiment set-up in order to investigate the transduction mechanism beneath them. The statistical treatment of the psychoacoustic data obtained has been performed by Two and Three Factors -Probit (Probability Unit) Analysis. Results: The Probit Analysis makes it possible to obtain the model coefficients and to fit 'Probit Planes and Surfaces' to the experimental data in order to study and predict the simultaneous effects produced by ITD and IAD in the listeners' psychoacoustic perceptions at several Sensation Levels (SL). Conclusion: The approach used here is appropriate for the analysis of this kind of binary response and it also offers a simple way to obtain psychophysical responses that can be related to neurophysiological phenomena. It is argued that this fact may lead to another way to access neural information through psychoacoustic experiments, without needing invasive methods.

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“…In order to model the direction dependency of the frequency response of the ears, HRTF have been developed [6]. These functions summarize the filtering effect of head, torso and pinna, for each direction and distance of a sound source [7], [8]. Localization then becomes a search for the pair of left and right HRTF that produces the highest correlation value when applied to the incoming signals.…”

Section: Introductionmentioning

confidence: 99%

“…Examples of these implementations include an accurate human head replica [7], the outer structure of a robot head [2], [17] and a widely separated array of two microphones with small ear-like structures [18]. Shieh et al [19] used a 12-microphone 19 cm semi-spherical array to localize sounds, in which a set of fuzzy-logic estimators use the level at each microphone to determine the sound direction.…”

Section: Introductionmentioning

confidence: 99%

Design of a Compact Sound Localization Device on a Stand-Alone FPGA-Based Platform

Kugler

Tossavainen

Kuroyanagi

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYSound localization systems are widely studied and have several potential applications, including hearing aid devices, surveillance and robotics. However, few proposed solutions target portable systems, such as wearable devices, which require a small unnoticeable platform, or unmanned aerial vehicles, in which weight and low power consumption are critical aspects. The main objective of this research is to achieve real-time sound localization capability in a small, self-contained device, without having to rely on large shaped platforms or complex microphone arrays. The proposed device has two surface-mount microphones spaced only 20 mm apart. Such reduced dimensions present challenges for the implementation, as differences in level and spectra become negligible, and only timedifference of arrival (TDoA) can be used as a localization cue. Three main issues have to be addressed in order to accomplish these objectives. To achieve real-time processing, the TDoA is calculated using zero-crossing spikes applied to the hardware-friendly Jeffers model. In order to make up for the reduction in resolution due to the small dimensions, the signal is upsampled several-fold within the system. Finally, a coherence-based spectral masking is used to select only frequency components with relevant TDoA information. The proposed system was implemented on a fieldprogrammable gate array (FPGA) based platform, due to the large amount of concurrent and independent tasks, which can be efficiently parallelized in reconfigurable hardware devices. Experimental results with white-noise and environmental sounds show high accuracies for both anechoic and reverberant conditions.

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Advanced Binaural Sound Localization in 3-D for Humanoid Robots

Cited by 47 publications

References 22 publications

Sound source localization and speech enhancement with sparse Bayesian learning beamforming

Sound source localization and speech enhancement with sparse Bayesian learning beamforming

Psychoacoustic behavior of human listeners in lateralization judgments of binaural stimuli

Design of a Compact Sound Localization Device on a Stand-Alone FPGA-Based Platform

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