- •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
108 |
6 Temporal Sensations of the Sound Signal |
a
b
Fig. 6.13 Probability match to the beat calculated by τ1 as a function of the fundamental frequency F0a. (a) In-phase condition. (b) Random condition. The different symbols indicate the beat frequency as the secondary fundamental frequencies, f: , 2 Hz; , 4 Hz; , 8 Hz; 16 Hz
6.4 Loudness
6.4.1 Loudness of Sharply Filtered Noise
This study examines correspondences between the perceived loudness of band-pass noise and properties of the ACF for center frequencies of 250, 500, and 1000 Hz. The bandwidth of the source signal was controlled using a 2068 dB/octave sharp
6.4 Loudness |
109 |
filter that parametrically altered the ACF of the filtered, source signal. The scale value of loudness was obtained using the paired-comparison method. Results show that loudness of a pure tone is greater than that of sharply filtered noises. Loudness of band-pass noise increases with increasing effective duration of the ACF (τe) of the source signal, which reflects the degree of repetitive structure in the signal. Thus, the loudness of band-pass noise inside the critical band is not constant.
Previous studies on the relationship between loudness and the bandwidth of noise have concluded that for sounds having the same SPL, loudness remains constant as bandwidth increases, up until the bandwidth reaches the “critical band.” For bandwidths larger than the critical band, loudness increases with bandwidth (Zwicker et al., 1957). The spectral characteristics of the filters used in those studies were not specified, except by Greenwood (1961a,b). Mathews and Pfafflin (1965) suggested that loudness of band-pass noises might differ between that using an actual filter and that using an ideal (rectangular shape) filter. An actual filter passes not only frequencies within the band defined by the −3 dB attenuation at the low and high cut-off frequencies, but also at frequencies outside the band. The response of the filter outside its −3 dB bandwidth greatly affects the repetitive feature of the signal (temporal coherence), represented by the effective duration τe that is extracted from ACF representations (Fig. 5.1; Ando, 1998; Ando et al., 1999). Such sharp filters may exist in the auditory system for high frequencies (Katsuki et al., 1958). In any case, a roll-off of more than 1000 dB/octave is required. The loudness of a sharply (1080 dB/octave) filtered noise increases as the effective duration of the normalized ACF (τe) increases, even if the bandwidth of the signal is within the critical band. It is worth noting that we observed that when the subsequent reverberation time (Tsub) of a sound field increases, effective duration τe also increases (Ando, 1998).
The purpose of this study was to examine the loudness of the band-pass noise in terms of factors extracted from the ACF. It is assumed that when the SPL is fixed at a constant value, the scale value of loudness S is expressed by
S = SL = fL(τ1, φ1, τe, D) |
(6.8) |
where the factors are defined in Section 5.2; Wφ(0) is excluded in the above equation because the center frequency of the noise is fixed and is represented by τ1, and D is the duration of the sound signal. As is well known, the sampling frequency of the sound wave should be more than the twice the maximum audio frequency. Thus, the value 10log (0)/ (0)ref is far more accurate than any factor based on the envelope of the waveform, (0)ref being the reference. The difference between them is prominent for an impulsive sound. It is worth noting that loudness does not depend on the IACC under conditions in which the SPL at both ear entrances is fixed. This confirms the results obtained using headphone reproduction (Chernyak and Dubrovsky, 1968; Dubrovskii and Chernyak, 1969).
How do signal and filter parameters affect the shape of the ACF and the features derived from it? A random generator produced white noise and then filtered it. The source signal of band-pass noises is characterized in terms of their ACFs as shown in Fig. 6.14. Bandwidth ( f) was changed by using a sharp filter with the cutoff
110 |
6 Temporal Sensations of the Sound Signal |
a
b
c
Fig. 6.14 Examples of the NACF analyzed for the center frequency of 500 Hz. The filter bandwidth F: (a) 0 Hz, (b) 40 Hz, (c) 80 Hz, (d) 160 Hz, (e) 320 Hz
slope of 2068 dB/octave, which was realized by a combination of two filters. Factors of τ1, τe, and φ1 analyzed are shown in Fig. 6.15. In fact, the filter bandwidth of 0 Hz included only its slope component. All source signals were the same SPL at 74 dBA, which was accurately adjusted by measurement of the ACF at the origin of the delay time, (0). As one can readily see, whereas filter bandwidth has absolutely no effect on the signal’s dominant periodicity (as reflected by τ1), it has a profound effect on the slope of the ACF envelope (effective duration, as reflected by τe) and a lesser effect on the relative height of the peak associated with the dominant periodicity φ1.
Loudness judgement experiments utilized paired comparison tests in which the ACF of the band-pass noise was changed. A headphone delivered the same sound signal to the two ears. Thus, the IACC was kept constant at nearly unity. Sound signals were digitized at a sampling frequency of 48 kHz. Five subjects with normal
6.4 Loudness |
111 |
d
e
Fig. 6.14 (continued)
hearing participated in the experiment. They were seated in an anechoic chamber and asked to judge which of two paired sound signals was perceived to be louder. Stimulus durations were 1.0 s, rise and fall times were 50 ms, and silent intervals between the stimuli were 0.5 s. A silent interval of 3.0 s separated each pair of stimuli, and the pairs were presented in random order.
Fifty responses (5 subjects × 10 sessions) to each stimulus were obtained. Consistency tests indicated that all subjects had a significant (p < 0.05) ability to discriminate loudness. The test of agreement also indicated that there was significant (p < 0.05) consensus among all subjects. A scale value of loudness was obtained by applying the law of comparative judgment (Thurstone’s case V) and was confirmed by goodness of fit.
The relationship between the scale value of loudness and the filter bandwidth is shown in Fig. 6.16. The scale value difference of 1.0 corresponds to about 1 dB due to the preliminary experiment. For all three-center frequencies (250, 500, 1000 Hz), the scale value of loudness is maximal for the pure tone with the infinite value of τe and large bandwidths, with minima at smaller bandwidths (40, 80, 160 Hz, respectively). From the dependence of τe on filter bandwidth, we found that loudness increases with increasing τe almost within the “critical bandwidth.” Results of analysis of variance for the scale values of loudness indicated that for all center frequencies tested, the scale values for the loudness of pure tones were significantly larger than those for other band-pass noises within the critical band
112 |
6 Temporal Sensations of the Sound Signal |
Fig. 6.15 Measured factors extracted from the ACF of the source signal as a function of the bandwidth. Different symbols indicate different frequencies. , 250 Hz; , 500 Hz; , 1000 Hz. (a) Delay time of the first peak of ACF (τ1). (b) Amplitude of the first peak of the ACF (φ1). (c) Effective duration of ACF (τe)
(p < 0.01). When the effects of changes in the reverberation time Tsub of the sound field on loudness are taken into account, the conclusion is that the factor τe, a measure of repetitive features of the sound signal, contributed to the loudness that is perceived (Merthayasa et al., 1994).
Consequently, loudness of the band-pass noise with identical SPL was not constant within the critical band. Also, loudness of the pure tone was significantly larger than that of sharply filtered noises, and loudness increased with increasing τe within the critical band. Therefore, Equation (6.8) within the critical band may be reduced by
S = SL = fL(τ1) + fL(τe) |
(6.9) |
In fact, MEG records of auditory-evoked magnetic fields showed that the N1m magnitude decreases with increasing bandwidth when the bandwidth is less than the critical bandwidth. This N1m peak magnitude also increases with increasing bandwidth beyond the critical band (Soeta et al., 2005).
6.4 Loudness |
113 |
Fig. 6.16 Scale values of loudness as a function of the bandwidth of noise. Different symbols indicate the scale values obtained with different subjects. (a) f c = 250 Hz. (b) f c = 500 Hz. (c) f c = 1000 Hz
