- •Preface
- •Acknowledgments
- •Contents
- •1 Introduction
- •1.1 Auditory Temporal and Spatial Factors
- •1.2 Auditory System Model for Temporal and Spatial Information Processing
- •2.1 Analysis of Source Signals
- •2.1.1 Power Spectrum
- •2.1.2 Autocorrelation Function (ACF)
- •2.1.3 Running Autocorrelation
- •2.2 Physical Factors of Sound Fields
- •2.2.1 Sound Transmission from a Point Source through a Room to the Listener
- •2.2.2 Temporal-Monaural Factors
- •2.2.3 Spatial-Binaural Factors
- •2.3 Simulation of a Sound Field in an Anechoic Enclosure
- •3 Subjective Preferences for Sound Fields
- •3.2.1 Optimal Listening Level (LL)
- •3.2.4 Optimal Magnitude of Interaural Crosscorrelation (IACC)
- •3.3 Theory of Subjective Preferences for Sound Fields
- •3.4 Evaluation of Boston Symphony Hall Based on Temporal and Spatial Factors
- •4.1.1 Brainstem Response Correlates of Sound Direction in the Horizontal Plane
- •4.1.2 Brainstem Response Correlates of Listening Level (LL) and Interaural Crosscorrelation Magnitude (IACC)
- •4.1.3 Remarks
- •4.2.2 Hemispheric Lateralization Related to Spatial Aspects of Sound
- •4.2.3 Response Latency Correlates of Subjective Preference
- •4.3 Electroencephalographic (EEG) Correlates of Subjective Preference
- •4.3.3 EEG Correlates of Interaural Correlation Magnitude (IACC) Changes
- •4.4.1 Preferences and the Persistence of Alpha Rhythms
- •4.4.2 Preferences and the Spatial Extent of Alpha Rhythms
- •4.4.3 Alpha Rhythm Correlates of Annoyance
- •5.1 Signal Processing Model of the Human Auditory System
- •5.1.1 Summary of Neural Evidence
- •5.1.1.1 Physical Characteristics of the Ear
- •5.1.1.2 Left and Right Auditory Brainstem Responses (ABRs)
- •5.1.1.3 Left and Right Hemisphere Slow Vertex Responses (SVRs)
- •5.1.1.4 Left and Right Hemisphere EEG Responses
- •5.1.1.5 Left and Right Hemisphere MEG Responses
- •5.1.2 Auditory Signal Processing Model
- •5.2 Temporal Factors Extracted from Autocorrelations of Sound Signals
- •5.3 Auditory Temporal Window for Autocorrelation Processing
- •5.5 Auditory Temporal Window for Binaural Processing
- •5.6 Hemispheric Specialization for Spatial Attributes of Sound Fields
- •6 Temporal Sensations of the Sound Signal
- •6.1 Combinations of Temporal and Spatial Sensations
- •6.2 Pitch of Complex Tones and Multiband Noise
- •6.2.1 Perception of the Low Pitch of Complex Tones
- •6.2.3 Frequency Limits of Missing Fundamentals
- •6.3 Beats Induced by Dual Missing Fundamentals
- •6.4 Loudness
- •6.4.1 Loudness of Sharply Filtered Noise
- •6.4.2 Loudness of Complex Noise
- •6.6 Timbre of an Electric Guitar Sound with Distortion
- •6.6.3 Concluding Remarks
- •7 Spatial Sensations of Binaural Signals
- •7.1 Sound Localization
- •7.1.1 Cues of Localization in the Horizontal Plane
- •7.1.2 Cues of Localization in the Median Plane
- •7.2 Apparent Source Width (ASW)
- •7.2.1 Apparent Width of Bandpass Noise
- •7.2.2 Apparent Width of Multiband Noise
- •7.3 Subjective Diffuseness
- •8.1 Pitches of Piano Notes
- •8.2 Design Studies of Concert Halls as Public Spaces
- •8.2.1 Genetic Algorithms (GAs) for Shape Optimization
- •8.2.2 Two Actual Designs: Kirishima and Tsuyama
- •8.3 Individualized Seat Selection Systems for Enhancing Aural Experience
- •8.3.1 A Seat Selection System
- •8.3.2 Individual Subjective Preference
- •8.3.3 Distributions of Listener Preferences
- •8.5 Concert Hall as Musical Instrument
- •8.5.1 Composing with the Hall in Mind: Matching Music and Reverberation
- •8.5.2 Expanding the Musical Image: Spatial Expression and Apparent Source Width
- •8.5.3 Enveloping Music: Spatial Expression and Musical Dynamics
- •8.6 Performing in a Hall: Blending Musical Performances with Sound Fields
- •8.6.1 Choosing a Performing Position on the Stage
- •8.6.2 Performance Adjustments that Optimize Temporal Factors
- •8.6.3 Towards Future Integration of Composition, Performance and Hall Acoustics
- •9.1 Effects of Temporal Factors on Speech Reception
- •9.2 Effects of Spatial Factors on Speech Reception
- •9.3 Effects of Sound Fields on Perceptual Dissimilarity
- •9.3.1 Perceptual Distance due to Temporal Factors
- •9.3.2 Perceptual Distance due to Spatial Factors
- •10.1 Method of Noise Measurement
- •10.2 Aircraft Noise
- •10.3 Flushing Toilet Noise
- •11.1 Noise Annoyance in Relation to Temporal Factors
- •11.1.1 Annoyance of Band-Pass Noise
- •11.2.1 Experiment 1: Effects of SPL and IACC Fluctuations
- •11.2.2 Experiment 2: Effects of Sound Movement
- •11.3 Effects of Noise and Music on Children
- •12 Introduction to Visual Sensations
- •13 Temporal and Spatial Sensations in Vision
- •13.1 Temporal Sensations of Flickering Light
- •13.1.1 Conclusions
- •13.2 Spatial Sensations
- •14 Subjective Preferences in Vision
- •14.1 Subjective Preferences for Flickering Lights
- •14.2 Subjective Preferences for Oscillatory Movements
- •14.3 Subjective Preferences for Texture
- •14.3.1 Preferred Regularity of Texture
- •15.1 EEG Correlates of Preferences for Flickering Lights
- •15.1.1 Persistence of Alpha Rhythms
- •15.1.2 Spatial Extent of Alpha Rhythms
- •15.2 MEG Correlates of Preferences for Flickering Lights
- •15.2.1 MEG Correlates of Sinusoidal Flicker
- •15.2.2 MEG Correlates of Fluctuating Flicker Rates
- •15.3 EEG Correlates of Preferences for Oscillatory Movements
- •15.4 Hemispheric Specializations in Vision
- •16 Summary of Auditory and Visual Sensations
- •16.1 Auditory Sensations
- •16.1.1 Auditory Temporal Sensations
- •16.1.2 Auditory Spatial Sensations
- •16.1.3 Auditory Subjective Preferences
- •16.1.4 Effects of Noise on Tasks and Annoyance
- •16.2.1 Temporal and Spatial Sensations in Vision
- •16.2.2 Visual Subjective Preferences
- •References
- •Glossary of Symbols
- •Abbreviations
- •Author Index
- •Subject Index
Chapter 6
Temporal Sensations of the Sound Signal
The basic perceived attributes of sound can be divided into those related to a sound’s perceived location in space (spatial sensations) and those qualities that distinguish different sounds independent of location (temporal sensations). Spatial sensations include sound location, size (apparent source width, ASW), and diffuseness. These subjective attributes are mainly subserved by the binaural system and can be described in terms of the interaural correlation function IACF (Chapter 7). Nonspatial and subjective attributes of sound include pitch, loudness, timbre, and duration. These perceptual qualities are grouped under the rubric of “temporal sensations” because they can be described in terms of temporal factors extracted from the monaural autocorrelation function ACF. Factors associated with temporal sensations typically predominate in neuronal responses from the left cerebral hemisphere (Fig. 5.1), while those associated with spatial sensations predominate in responses from the right hemisphere (Ando, 2006).
When a source signal is produced in a sound field, the properties of the sound field can influence the perception of nonspatial attributes. For example, reverberation time can affect loudness (Ando, 1998) and reverberations can degrade the pitches of unresolved harmonics (Sayles and Winter, 2008). Here we will discuss only the perceptual qualities of sounds in the absence of reverberation.
6.1 Combinations of Temporal and Spatial Sensations
The model outlined in Chapter 5 quite naturally leads to a division of primary sensations into two main categories: temporal sensations and spatial sensations. To begin with, we will discuss the relationship of subjective sensations to physical factors.
Neuropsychological models of perception attempt to describe relations between the physical attributes of external stimuli and the internal sensations they evoke. Whereas physical attributes can be publicly measured, sensations must be revealed to us either by direct experience or the overt perceptual judgments of others. Models of perception therefore involve finding mappings between physical attributes and mental, perceptual variables. Mental variables in turn are reflections of underlying
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DOI 10.1007/b13253_6, C Springer Science+Business Media, LLC 2009 |
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6 Temporal Sensations of the Sound Signal |
functional brain states. Psychophysical models of perception therefore include both phenomenological models that map physical stimulus variables directly onto patterns of perception and causal, mechanistic psychoneural models that first map stimulus attributes to brain states, and then brain states to mental states (experiences).
In psychophysical models, perceptual attributes associated with a given sensation can depend upon multiple physical factors, such that a single sensation j may not be well described only in terms of a single factor. Let Xi(i = 1, 2, . . ., I) be physical factors representing cues influencing any primary sensation (temporal and spatial sensations as mentioned above), in where J is a number of significant physical factors and I is the total number of physical factors, then similar to Equation (3.5), a sensation Sj may be expressed by
Sj = f(x1, x2, ... x1), j = 1, 2, ..., J |
(6.1) |
If physical factors are orthogonal to each other and contribute independently to a given sensation, then Sj may be expressed by a linear combination, such that,
Sj = f(x1) + f(x2) + ... + f(xI), j = 1, 2, ..., J |
(6.2) |
For example, let us consider the scale value of loudness, which might be described by not only the sound energy (0) and the pitch τ1, but also by repetitive feature of the signal (φ1 and/or τe) and the duration of the signal D, as expressed by Equation (6.9).
Here, the question arises as to whether or not a single sensation is independent of other sensations. The simplest case with two physical factors x1 and x2 is described in Equation (6.2) so that
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S1 = f1(x1) + f1(x2), j = 1 |
(6.3) |
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S2 = f2(x1) + f2(x2), j = 2 |
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The correlation coefficient between S1 and S2 is given by |
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r12 = |
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= f1 |
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+ f1 |
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+ f1 |
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+ f1 |
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(6.4) |
S1 S2 |
(x1) f2(x1) |
(x2) f2(x2) |
(x1) f2(x2) |
(x2) f2(x1) |
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and is not zero, because in general, the first and second terms of the right-hand side are not always zero. Previously, it was believed that these perceptual attributes are largely independent of each other. For example, timbre is independent and usually not much affected by loudness (50–90 dB SPL), pitch (F0: 200–400 Hz), or duration (100–600 ms), within limits. And we can readily identify musical instruments by their timbres irrespective of how loudly and how long any arbitrary notes are being played. However, more rigorously, we shall discuss sensations in relation to the possible dimension of physical factors.
In our auditory model, we consider differences in response patterns between the cerebral hemispheres of human listeners. Here, temporal factors are more prominent in the left hemisphere, whereas spatial factors are more prominent in the right hemisphere. Models in which an internal variable associated with each hemisphere