HRTF Sound Localization

Rothbucher, Martin; Kronmüller, David; Đurković, Marko; Habigt, Tim; Diepold, Klaus

doi:10.5772/14773

Cited by 7 publications

(6 citation statements)

References 10 publications

(14 reference statements)

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“…To develop our implementation of both of these methods, we tested using the same HRTF dataset that the authors in both papers used to obtain results [19]. Our implementation of the cross-convolution method produced similar results to those reported in [18,9] using speech sounds. For the Speech Prefilter method, we found that the performance of our implementation of this method was strongly dependent on the specific speech utterance used.…”

Section: Polar Angle Estimationmentioning

confidence: 81%

“…Two reference methods are tested: The first reference method is the Cross-Convolution method [18,9], which is a full-sphere localization method, and the second reference method is the Speech Prefilter method which is a median plane localization method [8]. To develop our implementation of both of these methods, we tested using the same HRTF dataset that the authors in both papers used to obtain results [19].…”

Section: Polar Angle Estimationmentioning

confidence: 99%

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Robust Full-Sphere Binaural Sound Source Localization

Hammond

Jackson

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a novel method for full-sphere binaural sound source localization that is designed to be robust to real world recording conditions. A mask is proposed that is designed to remove diffuse noise and early room reflections. The method makes use of the interaural phase difference (IPD) for lateral angle localization and spectral cues for polar angle localization. The method is tested using different HRTF datasets to generate the test data and training data. The method is also tested with the presence of additive noise and reverberation. The method outperforms the state of the art binaural localization methods for most testing conditions.

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Section: Polar Angle Estimationmentioning

confidence: 81%

Section: Polar Angle Estimationmentioning

confidence: 99%

Robust Full-Sphere Binaural Sound Source Localization

Hammond

Jackson

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…In this paper, slight modifications are made to the reference methods to improve their robustness to the testing conditions, while the spirit of the methods are retained. The reference methods are the Cross-Convolution method [4,3], the Speech Prefilter method [5] and the MUSIC (MUltiple SIgnal Classification) Signal Subspace method [6]. Our implementation of these methods is described in [19].…”

Section: Testing Proceduresmentioning

confidence: 99%

“…Finally, for robustness to different sound types and convolutive noise provided by the recording equipment, linear regression is used to remove the slow varying component in the spectra of the binaural sound received at both ears of the listener. The proposed method is compared with three state of the art reference methods [3,4,5,6], which have been selected for their different approaches to binaural sound source localization.…”

Section: Introductionmentioning

confidence: 99%

Robust Full-sphere Binaural Sound Source Localization Using Interaural and Spectral Cues

Hammond

Jackson

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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A binaural sound source localization method is proposed that uses interaural and spectral cues for localization of sound sources with any direction of arrival on the full-sphere. The method is designed to be robust to the presence of reverberation, additive noise and different types of sounds. The method uses the interaural phase difference (IPD) for lateral angle localization, then interaural and spectral cues for polar angle localization. The method applies different weighting to the interaural and spectral cues depending on the estimated lateral angle. In particular, only the spectral cues are used for sound sources near or on the median plane.

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“…This is of interest in robot perception (e.g. for event detection and localization [6], [7]), where the receiver's transfer functions can be measured beforehand. For humans, this problem is restricted to two receivers (human ears) where functions of left and right pairs of HRTFs are mapped to their measurement directions in place of SSL directions.…”

Section: Introductionmentioning

confidence: 99%

Gaussian process models for HRTF based 3D sound localization

Luo

Zotkin

Duraiswami

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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The human ability to localize sound-source direction using just two receivers is a complex process of direction inference from spectral cues of sound arriving at the ears. While these cues can be described using the well-known head-related transfer function (HRTF) concept, it is unclear as to how densely HRTF must be sampled and whether a higher-order representation is employed in localization. We propose a class of binaural sound source localization models to answer these two questions. First, using the sound received by two ears, we derive several binaural features that are invariant to the sound source signal. Second, these are implicitly mapped to a highdimensional reproducing kernel Hilbert space via a Gaussian process regression model for feature-direction tuples. Lastly, the features that are most relevant in the model are found via an efficient forward subset-selection method. Experimental results are shown for HRTFs belonging to the CIPIC database.

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HRTF Sound Localization

Cited by 7 publications

References 10 publications

Robust Full-Sphere Binaural Sound Source Localization

Robust Full-Sphere Binaural Sound Source Localization

Robust Full-sphere Binaural Sound Source Localization Using Interaural and Spectral Cues

Gaussian process models for HRTF based 3D sound localization

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