- •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
10.3 Flushing Toilet Noise |
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10.3 Flushing Toilet Noise
The purpose of this study is to identify factors of the flushing noise of an upstairs toilet, which despite having a low SPL caused annoyance for an apartment resident. We analyzed the temporal and spatial factors of the flushing noise from an upstairs toilet to the head position on a bed, because the resident was very annoyed during sleep. The noise signals were picked up by half-inch condenser microphones placed at two ear entrances on the spherical dummy head, which had been used for the aircraft noise measurements mentioned in the previous section.
The plans of the upstairs and downstairs are shown in Fig. 10.7, wherein recording was performed on two nights (Kitamura et al., 2002). During the measurement, all windows and a bedroom door were closed, and the air conditioner was turned off. The measured temporal factors extracted from the ACF are shown in Fig. 10.8. Solid lines indicate values for a typical example of the flushing toilet noise, and
Fig. 10.7 Plans of upstairs and downstairs in an apartment. The flushing noise of an upstairs toilet was recorded on a bed downstairs (X)
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dotted lines indicate the background noise. The measurement time was 5 s. The values of all factors were obtained with the integration interval of 0.5 s and the running interval of 100 ms.
As shown in Fig. 10.8a, the SPL measured by ll(0) for the flushing toilet noise was between 30 and 35 dBA, but the background noise was about 23 dBA. Thus, the maximum signal-to-noise ratio was 12 dBA. If the difference between the background noise level and the noise signal level is greater than 10 dB, the background noise does not affect significantly the noise signal measurement (Beranek, 1971). As shown in Fig. 10.8b and c, the τe value for the flushing toilet noise exceeded 100 ms with φ1 > 0.5, and τe < 0.1 ms and φ1 < 0.0.1 of the background noise throughout
Fig. 10.8 Measured factors extracted from the running ACF. Solid line indicates values for the flushing toilet noise, and dotted line indicates the background noise. (a) ll(0). (b) τe.
(c) φ1. (d) τ1. The values of all factors were obtained every 100 ms with an integration interval of 0.5 s
10.3 Flushing Toilet Noise |
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the measurement time. Thus, the flushing toilet noise had much more repetitive features than did the background noise. It has been reported that loudness increases in proportion to the value τe (see Section 6.4; Merthayasa and Ando, 1996). The value of τe for the flushing toilet noise was the largest near the peak of ll(0), as shown in Fig. 10.8a and b. The value of τ1 for the flushing toilet noise had a discrete value at 3.6 ms, which means that the perceived pitch was 275 Hz (Fig. 10.6d). The background noise did not have any clear pitch and tonal components, similar to white noise. These are clearly demonstrated in Fig. 10.9, which shows examples of the measured normalized ACF at t = 0.1 s, t = 0.9 s, and t = 2.5 s. The corresponding spectra are shown in Fig. 10.10. In addition, the measured special factors extracted from the IACF are shown in Fig. 10.11a–c. The IACC value for the flushing toilet
Fig. 10.9 Examples of the NACF analyzed. (a) Background noise measured at t = 0.1 s. (b and c) Flushing toilet noise measured at t = 0.9 s and 2.5 s, respectively
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Fig. 10.10 Power spectra of noise sources. (a) Background noise measured at t = 0.1 s. (b and c) Flushing toilet noise measured at t = 0.9 s and 2.5 s, respectively
noise was much higher than that for the background noise (below 0.05) in the measurement time. Thus, no specific directions may be perceived for the background noise. On the contrary, all spatial factors, the IACC, τIACC, and WIACC of the flushing noise, changed dramatically as a function of time. These results signify that subjective diffuseness, localization of sound source, and the ASW of the flushing toilet noise changed greatly as a function of time. Judging from these results, a clear pitch and the value of τe increased the annoyance of the flushing toilet noise as discussed in Section 11.1, although the SPL was low.
Thus far, it was found that the temporal and spatial factors extracted from the ACF and IACF of the flushing toilet noise had specific characteristics. These facts
10.3 Flushing Toilet Noise |
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Fig. 10.11 Measured factors extracted from the running IACF. Solid line indicates values for the flushing toilet noise, and dotted line indicates the background noise. (a) IACC. (b) τIACC. (c) WIACC. The values of all factors were obtained every 100 ms with an integration interval of 0.5 s
imply that both temporal sensations and spatial sensations of the flushing toilet noise changed dramatically. According to our auditory signal processing model, temporal information is mainly processed in the left hemisphere, and spatial information is mainly processed in the right hemisphere (Ando, 1998). Thus, the flushing noise from an upstairs toilet may stimulate both the left and right hemispheres of this resident at the same time. This might partly explain why the resident felt that the flushing noise of an upstairs toilet was very annoying despite its low SPL.
