Measurement and Modeling of Depth Cue Combination: in Defense of Weak Fusion

Technology and applications for the rendering of virtual acoustic spaces are reviewed. Chapter 1 deals with acoustics and psychoacoustics. Chapters 2 and 3 cover cues to spatial hearing and review psychoacoustic literature. Chapter 4 covers signal processing and systems overviews of 3-D sound systems. Chapter 5 covers applications to computer workstations, communication systems, aeronautics and space, and sonic arts. Chapter 6 lists resources. This TM is a reprint of the 1994 book from Academic Press.

/pdf/3-d-sound-for-virtual-reality-and-multimedia-jq7hovdm4r.pdf

3-D sound for virtual reality and multimedia

Vol. 1 1. Neural Basis of Vision. 2. Color Vision. 3. Depth Perception. 4. Perception of Visual Motion. 5. Perceptual Organization in Vision. 6. Attention. 7. Visual Object Recognition. 8. Motor Control. 9. Neural Basis of Audition. 10. Auditory Perception and Cognition. 11. Music Perception and Cognition. 12. Speech Perception. 13. Neural Basis of Haptic Perception. 14. Touch and Haptics. 15. Perception of Pain and Temperature. 16. Taste. 17. Olfaction. Vol. 2 1. Kinds of Memory. 2. Models of Memory. 3. Cognitive Neuroscience. 4. Spatial Cognition. 5. Knowledge Representation. 6. Psycholinguistics. 7. Language Processing. 8. Problem Solving. 9. Reasoning. 10. Decision Making. 11. Concepts & Categorization. 12. Cognitive Development. 13. Culture & Cognition. Vol. 3 1. Associative Structures in Pavlovian and Instrumental Conditioning. 2. Learning: Laws and Models of Basic Conditioning. 3. Reinforcement Learning. 4. Neural Analysis of Learning in Simple Systems. 5. Learning Mutants. 6. Learning Instincts. 7. Perceptual Learning. 8. Spatial Learning. 9. Temporal Learning. 10. Role of Learning in Cognitive Development. 11. Language Acquisition. 12. Role of Learning in the Operation of Motivational Systems. 13. Emotional Plasticity. 14. Anatomy of Motivation. 15. Hunger Energy Homeostasis. 16. Thirst and Water-Salt Appetite. 17. Reproductive Motivation. 18. Social Behavior. 19. Addiction. Vol. 4 1. Representational Measurement Theory. 2. Signal Detection Theory. 3. Psychophysical Scaling. 4. Cognitive Neuropsychology. 5. Functional Brain Imaging. 6. Neural Network Modeling. 7. Parallel and Serial Processing. 8. Methodology and Statistics in Single-Subject Experiments. 9. Analysis, Interpretation, and Visual Presentation of Experimental Data. 10. Meta-Analysis. 11. Mathematical Modeling. 12. Analysis of Response Time Distributions. 13. Testing and Measurement. 14. Personality and Individual Differences. 15. Electrophysiology of Attention. 16. Single vs. Multiple Systems of Memory and Learning. 17. Infant Cognition. 18. Aging and Cognition.

Stevens' handbook of experimental psychology

This article describes techniques used to synthesize headphone-presented stimuli that simulate the ear-canal waveforms produced by free-field sources. The stimulus synthesis techniques involve measurement of each subject's free-field-to-eardrum transfer functions for sources at a large number of locations in free field, and measurement of headphone-to-eardrum transfer functions with the subject wearing headphones. Digital filters are then constructed from the transfer function measurements, and stimuli are passed through these digital filters. Transfer function data from ten subjects and 144 source positions are described in this article, along with estimates of the various sources of error in the measurements. The free-field-to-eardrum transfer function data are consistent with comparable data reported elsewhere in the literature. A comparison of ear-canal waveforms produced by free-field sources with ear-canal waveforms produced by headphone-presented simulations shows that the simulations duplicate free-field waveforms within a few dB of magnitude and a few degrees of phase at frequencies up to 14 kHz.

Headphone simulation of free‐field listening. I: Stimulus synthesis

Listeners reported the apparent spatial positions of wideband noise bursts that were presented either by loudspeakers in free field or by headphones. The headphone stimuli were digitally processed with the aim of duplicating, at a listener’s eardrums, the waveforms that were produced by the free‐field stimuli. The processing algorithms were based on each subject’s free‐field‐to‐eardrum transfer functions that had been measured at 144 free‐field source locations. The headphone stimuli were localized by eight subjects in virtually the same positions as the corresponding free‐field stimuli. However, with headphone stimuli, there were more front–back confusions, and source elevation seemed slightly less well defined. One subject’s difficulty with elevation judgments, which was observed both with free‐field and with headphone stimuli, was traced to distorted features of the free‐field‐to‐eardrum transfer function.

Headphone simulation of free-field listening. II: Psychophysical validation

A mathematical model based on statistical decision theory has been devised to represent the human auditory localization task. The known localization cues have been represented as Gaussian random variables, so that their interaction in a given experiment can be analyzed (and predicted) along the lines of classical detection/estimation theory. We have applied this technique to most of the horizontal and vertical localization experiments reported in the literature during the past ten years, encompassing over 200 subjects and 20 000 trials. Using a nonlinear regression program we have been able to estimate the standard deviations of four of the auditory localization cues, allowing objective comparison of their relative accuracy. The resulting model provides a relatively good fit to the published results on 40 localization experiments.Subject Classification: [43]65.62, [43]65.58, [43]65.35.

Model for auditory localization

Physical measurements of the transfer function from a free−field sound source to a microphone in the subject’s ear canal indicate that there are two independent localization cues generated by the pinna. For sound sources in the vertical median plane, there is a systematic change in the frequency response as a function of elevation angle, and a disparity between the left−ear and right−ear responses which also changes systematically with elevation angle. Independent psychophysical measurements indicate that these pinna cues are detectable by subjects, and both are used by subjects in vertical localization tasks.Subject Classification: 65.62, 65.75.

L. D. Braida

Papers

Model for auditory localization

Binaural pinna disparity: another auditory localization cue.