Relevant bibliographies by topics / Binaural localization

Academic literature on the topic 'Binaural localization'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Binaural localization"

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Snik, Ad F. M., Andy J. Beynon, Catharina T. M. van der Pouw, Emmanuel A. M. Mylanus, and Cor W. R. J. Cremers. "Binaural Application of the Bone-Anchored Hearing Aid." Annals of Otology, Rhinology & Laryngology 107, no. 3 (March 1998): 187–93. http://dx.doi.org/10.1177/000348949810700301.

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Most, but not all, hearing-impaired patients with air conduction hearing aids prefer binaural amplification instead of monaural amplification. The binaural application of the bone conduction hearing aid is more disputable, because the attenuation (in decibels) of sound waves across the skull is so small (10 dB) that even one bone conduction hearing aid will stimulate both cochleas approximately to the same extent. Binaural fitting of the bone-anchored hearing aid was studied in three experienced bone-anchored hearing aid users. The experiments showed that sound localization, and speech recognition in quiet and also under certain noisy conditions improved significantly with binaural listening compared to the monaural listening condition. On the average, the percentage of correct identifications (within 45°) in the sound localization experiment improved by 53% with binaural listening; the speech reception threshold in quiet improved by 4.4 dB. The binaural advantage in the speech-in-noise test was comparable to that of a control group of subjects with normal hearing listening monaurally versus binaurally. The improvements in the scores were ascribed to diotic summation (improved speech recognition in quiet) and the ability to separate sounds in the binaural listening condition (improved sound localization and improved speech recognition in noise whenever the speech and noise signals came from different directions). All three patients preferred the binaural bone-anchored hearing aids and used them all day.
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Wu, Xinyi, Zhenyao Wu, Lili Ju, and Song Wang. "Binaural Audio-Visual Localization." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (May 18, 2021): 2961–68. http://dx.doi.org/10.1609/aaai.v35i4.16403.

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Localizing sound sources in a visual scene has many important applications and quite a few traditional or learning-based methods have been proposed for this task. Humans have the ability to roughly localize sound sources within or beyond the range of the vision using their binaural system. However most existing methods use monaural audio, instead of binaural audio, as a modality to help the localization. In addition, prior works usually localize sound sources in the form of object-level bounding boxes in images or videos and evaluate the localization accuracy by examining the overlap between the ground-truth and predicted bounding boxes. This is too rough since a real sound source is often only a part of an object. In this paper, we propose a deep learning method for pixel-level sound source localization by leveraging both binaural recordings and the corresponding videos. Specifically, we design a novel Binaural Audio-Visual Network (BAVNet), which concurrently extracts and integrates features from binaural recordings and videos. We also propose a point-annotation strategy to construct pixel-level ground truth for network training and performance evaluation. Experimental results on Fair-Play and YT-Music datasets demonstrate the effectiveness of the proposed method and show that binaural audio can greatly improve the performance of localizing the sound sources, especially when the quality of the visual information is limited.
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Koehnke, Janet, and Patrick M. Zurek. "Localization and binaural detection with monaural and binaural amplification." Journal of the Acoustical Society of America 88, S1 (November 1990): S169. http://dx.doi.org/10.1121/1.2028743.

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Razak, Khaleel A., and Zoltan M. Fuzessery. "Functional Organization of the Pallid Bat Auditory Cortex: Emphasis on Binaural Organization." Journal of Neurophysiology 87, no. 1 (January 1, 2002): 72–86. http://dx.doi.org/10.1152/jn.00226.2001.

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This report maps the organization of the primary auditory cortex of the pallid bat in terms of frequency tuning, selectivity for behaviorally relevant sounds, and interaural intensity difference (IID) sensitivity. The pallid bat is unusual in that it localizes terrestrial prey by passively listening to prey-generated noise transients (1–20 kHz), while reserving high-frequency (<30 kHz) echolocation for obstacle avoidance. The functional organization of its auditory cortex reflects the need for specializations in echolocation and passive sound localization. Best frequencies were arranged tonotopically with a general increase in the caudolateral to rostromedial direction. Frequencies between 24 and 32 kHz were under-represented, resulting in hypertrophy of frequencies relevant for prey localization and echolocation. Most neurons (83%) tuned <30 kHz responded preferentially to broadband or band-pass noise over single tones. Most neurons (62%) tuned >30 kHz responded selectively or exclusively to the 60- to 30-kHz downward frequency-modulated (FM) sweep used for echolocation. Within the low-frequency region, neurons were placed in two groups that occurred in two separate clusters: those selective for low- or high-frequency band-pass noise and suppressed by broadband noise, and neurons that showed no preference for band-pass noise over broadband noise. Neurons were organized in homogeneous clusters with respect to their binaural response properties. The distribution of binaural properties differed in the noise- and FM sweep-preferring regions, suggesting task-dependent differences in binaural processing. The low-frequency region was dominated by a large cluster of binaurally inhibited neurons with a smaller cluster of neurons with mixed binaural interactions. The FM sweep-selective region was dominated by neurons with mixed binaural interactions or monaural neurons. Finally, this report describes a cortical substrate for systematic representation of a spatial cue, IIDs, in the low-frequency region. This substrate may underlie a population code for sound localization based on a systematic shift in the distribution of activity across the cortex with sound source location.
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Koehnke, Janet, Joan Besing, Christine Goulet, Marla Allard, and Patrick M. Zurek. "Speech intelligibility, localization, and binaural detection with monaural and binaural amplification." Journal of the Acoustical Society of America 92, no. 4 (October 1992): 2434. http://dx.doi.org/10.1121/1.404588.

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Ge, Zheng. "SVM-based Binaural Sound Source Localization." Journal of Information and Computational Science 12, no. 14 (September 20, 2015): 5459–67. http://dx.doi.org/10.12733/jics20106459.

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Craig, Rushby C., and Timothy R. Anderson. "Binaural sound localization using neural networks." Journal of the Acoustical Society of America 91, no. 4 (April 1992): 2415. http://dx.doi.org/10.1121/1.403229.

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Van Wanrooij, Marc M., and A. John Van Opstal. "Sound Localization Under Perturbed Binaural Hearing." Journal of Neurophysiology 97, no. 1 (January 2007): 715–26. http://dx.doi.org/10.1152/jn.00260.2006.

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This paper reports on the acute effects of a monaural plug on directional hearing in the horizontal (azimuth) and vertical (elevation) planes of human listeners. Sound localization behavior was tested with rapid head-orienting responses toward brief high-pass filtered (>3 kHz; HP) and broadband (0.5–20 kHz; BB) noises, with sound levels between 30 and 60 dB, A-weighted (dBA). To deny listeners any consistent azimuth-related head-shadow cues, stimuli were randomly interleaved. A plug immediately degraded azimuth performance, as evidenced by a sound level–dependent shift (“bias”) of responses contralateral to the plug, and a level-dependent change in the slope of the stimulus–response relation (“gain”). Although the azimuth bias and gain were highly correlated, they could not be predicted from the plug's acoustic attenuation. Interestingly, listeners performed best for low-intensity stimuli at their normal-hearing side. These data demonstrate that listeners rely on monaural spectral cues for sound-source azimuth localization as soon as the binaural difference cues break down. Also the elevation response components were affected by the plug: elevation gain depended on both stimulus azimuth and on sound level and, as for azimuth, localization was best for low-intensity stimuli at the hearing side. Our results show that the neural computation of elevation incorporates a binaural weighting process that relies on the perceived, rather than the actual, sound-source azimuth. It is our conjecture that sound localization ensues from a weighting of all acoustic cues for both azimuth and elevation, in which the weights may be partially determined, and rapidly updated, by the reliability of the particular cue.
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Razak, Khaleel A., and Zoltan M. Fuzessery. "GABA Shapes a Systematic Map of Binaural Sensitivity in the Auditory Cortex." Journal of Neurophysiology 104, no. 1 (July 2010): 517–28. http://dx.doi.org/10.1152/jn.00294.2010.

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A consistent organizational feature of auditory cortex is a clustered representation of binaural properties. Here we address two questions. What is the intrinsic organization of binaural clusters and to what extent does intracortical processing contribute to binaural representation. We address these issues in the auditory cortex of the pallid bat. The pallid bat listens to prey-generated noise transients to localize and hunt terrestrial prey. As in other species studied, binaural clusters are present in the auditory cortex of the pallid bat. One cluster contains neurons that require binaural stimulation to be maximally excited, and are commonly termed predominantly binaural (PB) neurons. These neurons do not respond to monaural stimulation of either ear but show a peaked sensitivity to interaural intensity differences (IID) centered near 0 dB IID. We show that the peak IID varies systematically within this cluster. The peak IID is also correlated with the best frequency (BF) of neurons within this cluster. In addition, the IID selectivity of PB neurons is shaped by intracortical GABAergic input. Iontophoresis of GABAA receptor antagonists on PB neurons converts a majority of them to binaurally inhibited (EI) neurons that respond best to sounds favoring the contralateral ear. These data indicate that the cortex does not simply inherit binaural properties from lower levels but instead sharpens them locally through intracortical inhibition. The IID selectivity of the PB cluster indicates that the pallid bat cortex contains an increased representation of the frontal space that may underlie increased localization accuracy in this region.
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Samson, Annie-Hélène, and Gerald S. Pollack. "Encoding of Sound Localization Cues by an Identified Auditory Interneuron: Effects of Stimulus Temporal Pattern." Journal of Neurophysiology 88, no. 5 (November 1, 2002): 2322–28. http://dx.doi.org/10.1152/jn.00119.2002.

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An important cue for sound localization is binaural comparison of stimulus intensity. Two features of neuronal responses, response strength, i.e., spike count and/or rate, and response latency, vary with stimulus intensity, and binaural comparison of either or both might underlie localization. Previous studies at the receptor-neuron level showed that these response features are affected by the stimulus temporal pattern. When sounds are repeated rapidly, as occurs in many natural sounds, response strength decreases and latency increases, resulting in altered coding of localization cues. In this study we analyze binaural cues for sound localization at the level of an identified pair of interneurons (the left and right AN2) in the cricket auditory system, with emphasis on the effects of stimulus temporal pattern on binaural response differences. AN2 spike count decreases with rapidly repeated stimulation and latency increases. Both effects depend on stimulus intensity. Because of the difference in intensity at the two ears, binaural differences in spike count and latency change as stimulation continues. The binaural difference in spike count decreases, whereas the difference in latency increases. The proportional changes in response strength and in latency are greater at the interneuron level than at the receptor level, suggesting that factors in addition to decrement of receptor responses are involved. Intracellular recordings reveal that a slowly building, long-lasting hyperpolarization is established in AN2. At the same time, the level of depolarization reached during the excitatory postsynaptic potential (EPSP) resulting from each sound stimulus decreases. Neither these effects on membrane potential nor the changes in spiking response are accounted for by contralateral inhibition. Based on comparison of our results with earlier behavioral experiments, it is unlikely that crickets use the binaural difference in latency of AN2 responses as the main cue for determining sound direction, leaving the difference in response strength, i.e., spike count and/or rate, as the most likely candidate.
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Dissertations / Theses on the topic "Binaural localization"

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Reid, Greg L. "Active binaural sound localization techniques, experiments and comparisons." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ39225.pdf.

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Wang, Qiang 1968. "Underwater object localization using a biomimetic binaural sonar." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80359.

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Thesis (S.M. in Oceanographic Engineering)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 1999.
Includes bibliographical references (leaves 85-89).
by Qiang Wang.
S.M.in Oceanographic Engineering
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Jansson, Conny. "Servostyrning med binaural ljudlokalisering." Thesis, Linköpings universitet, Institutionen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117605.

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People are usually directed towards each other in conversations, to make it easier to hear what is being said. Algorithms for voice and speech recognition works in a similar way, regarding the microphone direction towards the sound source. In this thesis in electronics has therefore a servo control with binaural sound localization been implemented on a microcontroller connected to two microphones. When people perceive sound, the brain can estimate the sound source direction by comparing the time taken by the sound reaching one ear to the other [1]. The difference in time is called the interaural time difference, and can be calculated using various techniques. An exploratory comparison between the techniques cross-correlation and cross-spectrum analysis was carried out before implementation. Advantages and disadvantages of each technique were evaluated at the same time. The result is a functioning servo control, that uses a cross correlation algorithm to calculate the interaural time difference, and controls a servo motor towards the sound source with a P-regulated error reduction method. The project was implemented on the microcontroller ATmega328P from Atmel without using floating point calculations. The thesis was carried out on behalf of the company Jetspark Robotics.
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Keyrouz, Fakheredine. "Efficient binaural sound localization for humanoid robots and telepresence applications." kostenfrei, 2008. http://mediatum2.ub.tum.de/doc/648977/648977.pdf.

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Benichoux, Victor. "Timing cues for azimuthal sound source localization." Phd thesis, Université René Descartes - Paris V, 2013. http://tel.archives-ouvertes.fr/tel-00931645.

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Azimuth sound localization in many animals relies on the processing of differences in time-of-arrival of the low-frequency sounds at both ears: the interaural time differences (ITD). It was observed in some species that this cue depends on the spectrum of the signal emitted by the source. Yet, this variation is often discarded, as humans and animals are assumed to be insensitive to it. The purpose of this thesis is to assess this dependency using acoustical techniques, and explore the consequences of this additional complexity on the neurophysiology and psychophysics of sound localization. In the vicinity of rigid spheres, a sound field is diffracted, leading to frequency-dependent wave propagation regimes. Therefore, when the head is modeled as a rigid sphere, the ITD for a given position is a frequency-dependent quantity. I show that this is indeed reflected on human ITDs by studying acoustical recordings for a large number of human and animal subjects. Furthermore, I explain the effect of this variation at two scales. Locally in frequency the ITD introduces different envelope and fine structure delays in the signals reaching the ears. Second the ITD for low-frequency sounds is generally bigger than for high frequency sounds coming from the same position. In a second part, I introduce and discuss the current views on the binaural ITD-sensitive system in mammals. I expose that the heterogenous responses of such cells are well predicted when it is assumed that they are tuned to frequency-dependent ITDs. Furthermore, I discuss how those cells can be made to be tuned to a particular position in space irregardless of the frequency content of the stimulus. Overall, I argue that current data in mammals is consistent with the hypothesis that cells are tuned to a single position in space. Finally, I explore the impact of the frequency-dependence of ITD on human behavior, using psychoacoustical techniques. Subjects are asked to match the lateral position of sounds presented with different frequency content. Those results suggest that humans perceive sounds with different frequency contents at the same position provided that they have different ITDs, as predicted from acoustical data. The extent to which this occurs is well predicted by a spherical model of the head. Combining approaches from different fields, I show that the binaural system is remarkably adapted to the cues available in its environment. This processing strategy used by animals can be of great inspiration to the design of robotic systems.
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Woodruff, John F. "Integrating Monaural and Binaural Cues for Sound Localization and Segregation in Reverberant Environments." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1332425718.

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Kyweriga, Michael. "The Synaptic Mechanisms Underlying Binaural Interactions in Rat Auditory Cortex." Thesis, University of Oregon, 2014. http://hdl.handle.net/1794/18442.

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The interaural level difference (ILD) is a sound localization cue first computed in the lateral superior olive (LSO) by comparing the loudness of sounds between the two ears. In the auditory cortex, one class of neurons is excited by contralateral but not ipsilateral monaural sounds. These "EO" neurons prefer ILDs where contralateral sounds are louder than ipsilateral sounds. Another class, the "PB" neurons, are unresponsive to monaural sounds but respond predominantly to binaural ILDs, when both ears receive simultaneous sounds of roughly equal loudness (0 ILD). Behavioral studies show that ILD sensitivity is invariant to increasing sound levels. However, in the LSO, ILD response functions shift towards the excitatory ear as sound level increases, indicating level-dependence. Thus, changes in firing rate can indicate either a change in sound location or sound level, or both. This suggests a transformation in level-sensitivity between the LSO and the perception of sound sources, yet the location of this transformation remains unknown. I performed recordings in the auditory cortex of the rat to test whether neurons were invariant to overall sound level. I found that with increasing sound levels, ILD responses were level-dependent, suggesting that level invariance of ILD sensitivity is not present in the rat auditory cortex. In general, neurons follow one of two processing strategies. The tuning of cortical cells typically follows the "inheritance strategy", such that the spiking output of the cell matches that of the excitatory synaptic input. However, cortical tuning can be modified by inhibition in the "local processing strategy". In this case, neurons are prevented from spiking at non-preferred stimuli by inhibition that overwhelms excitation. The tuning strategy of cortical neurons to ILD remains unknown. I performed whole-cell recordings in the anesthetized rat and compared the spiking output with synaptic inputs to ILDs within the same neurons. I found that the PB neurons showed evidence of the local processing strategy, which is a novel role for cortical inhibition, whereas the EO neurons utilized the inheritance strategy. This result suggests that an auditory cortical circuit computes sensitivity for midline ILDs. This dissertation includes previously published/unpublished co-authored material.
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Kim, Ui-Hyun. "Improvement of Sound Source Localization for a Binaural Robot of Spherical Head with Pinnae." 京都大学 (Kyoto University), 2013. http://hdl.handle.net/2433/180475.

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Schölling, Björn. "Binaural signal processing for source localization and noise reduction with applications to mobile robotics." Münster Verl.-Haus Monsenstein und Vannerdat, 2009. http://d-nb.info/994281242/04.

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Goeckel, Tom [Verfasser], Gerhard [Akademischer Betreuer] Lakemeyer, and Hermann [Akademischer Betreuer] Wagner. "Efficient Binaural Sound Localization in Noisy and Reverberant Environments / Tom Goeckel ; Gerhard Lakemeyer, Hermann Wagner." Aachen : Universitätsbibliothek der RWTH Aachen, 2015. http://d-nb.info/1130402738/34.

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Books on the topic "Binaural localization"

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Yin, Tom C. T., and Shigeyuki Kuwada. Binaural localization cues. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199233281.013.0012.

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Book chapters on the topic "Binaural localization"

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Nicoletti, M., Chr Wirtz, and W. Hemmert. "Modeling Sound Localization with Cochlear Implants." In The Technology of Binaural Listening, 309–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37762-4_12.

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May, T., S. van de Par, and A. Kohlrausch. "Binaural Localization and Detection of Speakers in Complex Acoustic Scenes." In The Technology of Binaural Listening, 397–425. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37762-4_15.

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Baumgartner, R., P. Majdak, and B. Laback. "Assessment of Sagittal-Plane Sound Localization Performance in Spatial-Audio Applications." In The Technology of Binaural Listening, 93–119. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37762-4_4.

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Song, Tao, and Jing Chen. "An Environment-Adaptation Based Binaural Localization Method." In Lecture Notes in Computer Science, 35–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02698-1_4.

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Le Goff, N., J. M. Buchholz, and T. Dau. "Modeling Horizontal Localization of Complex Sounds in the Impaired and Aided Impaired Auditory System." In The Technology of Binaural Listening, 121–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37762-4_5.

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Yin, Tom C. T. "Neural Mechanisms of Encoding Binaural Localization Cues in the Auditory Brainstem." In Integrative Functions in the Mammalian Auditory Pathway, 99–159. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4757-3654-0_4.

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Hwang, Do-hyeong, and Jong-suk Choi. "Real-Time Binaural Sound Source Localization Using Sparse Coding and SOM." In Intelligent Robotics and Applications, 582–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16584-9_56.

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Venkatesan, R., and A. Balaji Ganesh. "Unsupervised Auditory Saliency Enabled Binaural Scene Analyzer for Speaker Localization and Recognition." In Advances in Intelligent Systems and Computing, 337–50. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67934-1_30.

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Delić, Vlado, and Nataša Vujnović Sedlar. "Stereo Presentation and Binaural Localization in a Memory Game for the Visually Impaired." In Development of Multimodal Interfaces: Active Listening and Synchrony, 354–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12397-9_31.

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Schauer, Carsten, and Horst-Michael Gross. "A Model of Horizontal 360° Object Localization Based on Binaural Hearing and Monocular Vision." In Artificial Neural Networks — ICANN 2001, 1141–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44668-0_159.

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Conference papers on the topic "Binaural localization"

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Abdalla, Hisham, and Timothy K. Horiuchi. "Binaural spectral cues for ultrasonic localization." In 2008 IEEE International Symposium on Circuits and Systems - ISCAS 2008. IEEE, 2008. http://dx.doi.org/10.1109/iscas.2008.4541866.

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Yang, Qiang, and Yuanqing Zheng. "DeepEar: Sound Localization with Binaural Microphones." In IEEE INFOCOM 2022 - IEEE Conference on Computer Communications. IEEE, 2022. http://dx.doi.org/10.1109/infocom48880.2022.9796850.

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Schymura, Christopher, Juan Diego Rios Grajales, and Dorothea Kolossa. "Monte Carlo exploration for active binaural localization." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952204.

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Venkatesan, R., and A. Balaji Ganesh. "Full sound source localization of binaural signals." In 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2017. http://dx.doi.org/10.1109/wispnet.2017.8299750.

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Girija Ramesan, Karthik, Parth Suresh, and Prasanta Kumar Ghosh. "Subband Weighting for Binaural Speech Source Localization." In Interspeech 2018. ISCA: ISCA, 2018. http://dx.doi.org/10.21437/interspeech.2018-2173.

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Karthik, Girija Ramesan, and Prasanta Kumar Ghosh. "Subband Selection for Binaural Speech Source Localization." In Interspeech 2017. ISCA: ISCA, 2017. http://dx.doi.org/10.21437/interspeech.2017-954.

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Keyrouz, Fakheredine, and Klaus Diepold. "An Enhanced Binaural 3D Sound Localization Algorithm." In 2006 IEEE International Symposium on Signal Processing and Information Technology. IEEE, 2006. http://dx.doi.org/10.1109/isspit.2006.270883.

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Hammond, Benjamin R., and Philip J. B. Jackson. "Robust Full-Sphere Binaural Sound Source Localization." In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8462103.

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Tang, Duowei, Maja Taseska, and Toon van Waterschoot. "Supervised Contrastive Embeddings for Binaural Source Localization." In 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE, 2019. http://dx.doi.org/10.1109/waspaa.2019.8937177.

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Kaneko, Shoken, and Hannes Gamper. "Towards all-purpose full-sphere binaural localization." In 2022 30th European Signal Processing Conference (EUSIPCO). IEEE, 2022. http://dx.doi.org/10.23919/eusipco55093.2022.9909908.

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