- •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
34 |
3 Subjective Preferences for Sound Fields |
Fig. 7.14). To realize these conditions simultaneously, geometrically uneven surfaces for the side walls of the concert hall have been proposed (Ando and Sakamoto, 1988).
3.3 Theory of Subjective Preferences for Sound Fields
We will now put these results into theory. Because preference involves a limited number of orthogonal acoustic factors that are implicit in the sound signals arriving at both ears (Table 3.1), the scale value of any one-dimensional subjective response may be expressed as a function of these factors
S=f (x1, x2, . . . xI ). |
(3.5) |
A linear scale value for subjective preference can be derived using the law of comparative judgment or paired-comparisons tests (Thurstone, 1927; Mosteller, 1951; Gullikson, 1956; Torgerson, 1958) for both groups of subjects as well as for individuals (Ando, 1998). Through a series of experiments, it has been verified that four objective acoustic factors act independently of the scale value when two of the four factors are varied simultaneously, as indicated in Table 3.3. Results obtained in a series of experiments that used different source signals indicate that the four units of scale appear to be almost constant, so we can add individual scale values to obtain the total scale value (Ando, 1983),
S = f (x1) + f (x2) + f (x3) + f (x4) |
(3.6) |
= S1 + S2 + S3 + S3 |
|
where Si , i = 1, 2, 3, 4 is the scale value obtained relative to each objective factor. Equation (3.6) represents a four-dimensional continuum.
The dependence of the scale values on each objective factor is shown graphically in Fig. 3.5. From the nature of the scale value, it is convenient to set its value to zero at the most preferred conditions, as shown in this figure. Scale values of subjective preference obtained from other experimental series that used different music programs, yield similar results when each factor is normalized by its most preferred value. The following common formula is given:
Table 3.3 Subjective preference tests examining independent effects changing two of four orthogonal factors of the sound field
Factors |
LL |
t1 (SD) |
Tsub |
IACC |
LL |
– |
Ando and Okada1 |
Not examined |
Test B: Ando and Morioka |
|
|
|
|
(1981) |
t1 (SD) |
|
– |
Test A: Ando |
Ando and Imamura (1979); |
|
|
|
et al. (1982) |
Ando and Gottlob (1979) |
Tsub |
|
|
– |
Test C: Ando et al. (1983) |
1Unpublished (see Ando 1998).
3.3 |
Theory of Subjective Preferences for Sound Fields |
35 |
(a) |
(c) |
|
(b) |
(d) |
Fig. 3.5 Scale values of subjective preference obtained for simulated sound fields in an anechoic chamber, as a function of four normalized orthogonal factors of the sound field. Different symbols indicate scale values obtained from different source signals (Ando, 1985). (a) As a function of listening level, LL. The most preferred listening level, [LL]p = 0 dB. (b) As a function of first reflection time t1/[ t1]p. (c) As a function of later reverberation time Tsub/[Tsub]p. (d) As a function of interaural correlation magnitude IACC. The most preferred values [ t1]p and [Tsub]p are calculated by Equations (3.3) and (3.4), respectively. Even if different signals are used, consistency of scale values as a function of the normalized factor is maintained, fitting a single curve
Si ≈ −αi |xi |3/2 , i = 1, 2, 3, 4 |
(3.7) |
where xi is the normalized factor and the values of αi are weighting coefficients as listed in Table 3.4. If αι is close to zero, then a lesser contribution of the factor xi on subjective preference is signified.
Table 3.4 Four orthogonal factors of the sound field, and its weighting coefficients αi in Equation (3.7), which was obtained with a number of subjects
i |
xi |
|
αi |
|
|
xi > 0 |
xi < 0 |
||
|
|
|
||
|
|
|
|
|
1 |
20logP − 20log[p]p (dB) |
0.07 |
0.04 |
|
2 |
log( t1/[ t1]p) |
1.42 |
1.11 |
|
3 |
log(Tsub/[Tsub]p) |
|
0.45 + 0.75A |
2.36 – 0.42A |
4 |
IACC |
1.45 |
– |
|
|
|
|
|
|
36 |
3 Subjective Preferences for Sound Fields |
The factor x1 is given by the sound pressure level difference, measured by the A-weighted network, so that,
x1= 20 log P − 20log[P]p |
(3.8) |
P and [P]p being, respectively, the sound pressure or listening level (LL) present at a specific seat and the most preferred sound pressure that may be assumed at a particular seat position in the room under investigation:
x2 = log ( t1/[ t1]p) |
(3.9) |
x3 = log (Tsub/[Tsub]p) |
(3.10) |
x4= IACC |
(3.11) |
The values of [ t1]p and [Tsub]p may be calculated using Equations (3.1) and (3.4), respectively.
The scale value of preference has been formulated approximately in terms of the 3/2 power of the normalized factor, expressed in terms of the logarithm of the normalized factors, x1, x2, and x3. The remarkable fact is that the spatial binaural factor x4 = IACC is expressed in terms of the 3/2 power of its real values, indicating a greater contribution than those of the temporal parameters. The scale values are not greatly changed in the neighborhood of the most preferred conditions, but decrease rapidly outside this range. Since the experiments were conducted to find the optimal conditions, this theory remains valid in the range of preferred conditions tested for the four orthogonal factors. When t1 and Tsub are fixed near their preferred conditions, for example, the scale value of subjective preference calculated by Equation (3.6) for the LL and the IACC is demonstrated in Fig. 3.6. Agreement between cal-
Fig. 3.6 Scale values of subjective preference for the sound field with music motif A as a function of the listening level (LL) and as a parameter of the IACC (Ando and Morioka, 1981). (_ _ _ _): Calculated values based on Equation (3.6) taking the two factors into consideration; (____): Measured values
3.4 Evaluation of Boston Symphony Hall Based on Temporal and Spatial Factors |
37 |
culated values and observed ones are satisfactory, so that the independence of the listening level LL and the IACC on the scale value is achieved (Ando and Morioka, 1981). The same is true for the other two factors (Ando, 1985).
3.4Evaluation of Boston Symphony Hall Based on Temporal and Spatial Factors
As a typical example, we will consider the quality of the sound field at each seating position in an existing concert hall using the Symphony Hall in Boston, Massachusetts, as a model. Suppose that a single source is located at center stage, 1.2 m above the stage floor. Ear positions are receiving points situated at a height of 1.1 m above floor level. The 30 earliest reflections with their amplitudes, delay times, and directions of arrival at the listeners are taken into account using the image method.
Contour lines of the total scale value of preference, calculated for music motif B are shown in Fig. 3.7. The left plot (a) demonstrates the effects of the reflections from the sides on the stage in their original shape configuration. Adding angled reflecting sidewalls on the sides of the stage, as in right plot (b), may produce decreasing values of the IACC for substantial portions of the audience area, which increases the total preference value at each seat (compare left and right plots). In this calculation, reverberation time is assumed to be 1.8 s throughout the hall and the most preferred listening level, [LL]p = 20 log[P]p in Equation (3.10), is set for a point on the center line 20 m from the source position.
(a) |
(b) |
Fig. 3.7 Predicted effects of modified room dimensions on listener satisfaction. An example of calculating scale values with the four orthogonal factors using Equations (3.6) through (3.11). (a) Contour lines of the total scale value for Boston Symphony Hall, with original side walls on the stage. (b) Contour lines of the total scale values for the side walls optimized
38 |
3 Subjective Preferences for Sound Fields |
In order to further test the subjective preference theory, subjective preference judgments in another existing hall (Uhara Hall in Kobe, Japan) were performed using paired-comparison tests (PCT) at each set of seats. Here source locations on the stage were varied. The theory of subjective preference with orthogonal factors was reconfirmed (Sato et al., 1997; Ando, 1998). It was also shown that the theory holds at the condition of τ IACC = 0, i.e., a source at its optimal location at center stage. For other, off-center positions, preference values decrease.
Chapter 4
Electrical and Magnetic Responses
in the Central Auditory System
Four significant, orthogonal physical factors that describe temporal and spatial characteristics of sound fields in concert halls were discussed in the preceding chapter. The fields of physical, physiological, and psychological acoustics are deeply related to each other. If enough were known about how the brain analyzes nerve impulses from cochlea to cortex, the design of concert halls and other acoustic environments could proceed rationally, according to guidelines derived from the knowledge of these processes. This motivated us to make a sustained effort to describe important qualities of sound in terms of neural information processing in the auditory pathway and the rest of the brain.
Formulation of such a neurally grounded strategy for acoustic design has been initiated through a study of auditory-evoked electrical potentials, short-latency auditory brainstem responses (ABR) that are generated in the cochlea, brainstem, and midbrain, and longer-latency slow vertex responses (SVR) that are generated in the cerebral cortex. The ultimate goal of these experiments was to identify potential neuronal response correlates of subjective preference for the orthogonal acoustic parameters most important for the perception of sound fields. Using paired-comparison methods (Ando, 1977, 1983, 1985, 1998), we had found that particular ranges of the four factors were preferred by most listeners, such that reliable predictions of subjective preferences could be made.
In order to formulate a comprehensive model of signal processing in the central auditory system, early auditory brainstem responses (ABRs, 0–10 ms latency) were first examined to characterize signal flows in ascending auditory pathways and their possible functions at each level of processing. Then, cortical, longer-latency slow vertex responses (SVR) corresponding to subjective preferences were examined in relation to temporal and spatial factors. In the third stage, we investigated aspects of human electroencephalography (EEG) and the magnetoencephalography (MEG) responses that correspond to subjective preference. EEG and MEG signals in the alpha frequency band were analyzed using autocorrelations and crosscorrelations. Table 4.1 summarizes the acoustic factors, their corresponding percepts and preferences, and the neuronal correlates that were found.
Y. Ando, P. Cariani (Guest ed.), Auditory and Visual Sensations, |
39 |
DOI 10.1007/b13253_4, C Springer Science+Business Media, LLC 2009 |
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