There also appear to be common, possibly universal, neural response correlates of subjective preference that hold for both temporal and spatial factors and their associated perceptual attributes in both the auditory and visual modalities. These are related to the persistence, temporal coherence, and spatial extent of alpha rhythms in auditory and visual cortical populations. The alpha rhythms are signs of subjective preference, but it remains to be explained why some of the factors themselves have preferred values that generate primitive “aesthetic” valences. Some examples of the latter are subjective preferences for vibrato of musical notes, fluctuations in the rates of flickering lights, and less-than-absolute regularities in textures.

16.1 Auditory Sensations

16.1.1 Auditory Temporal Sensations

Table 16.1 presents an overview of auditory temporal sensations, such as loudness, pitch, timbre and duration, which are described by temporal factors that are features of the autocorrelation functions (ACFs) of sound signals. We want to be as clear as possible about the various dependencies of percepts on single and multiple factors. Loudness, for example, is a function of several factors, most notably sound energyp(0) and dominant periodicity or frequency τ1, but also effective duration τe (or φ1) as expressed by Equation (6.8). When the sound signal arrives from only directly in front, timbre is described by the factor of Wφ(0) extracted from the monaural autocorrelation function ACF. If the sound signal arrives from any direction other than

Table 16.1 Auditory temporal sensations in relation to the temporal factor extracted from the ACF. The resulting equation, figures or section are indicated at respective sensation

1X: Major factors, which have been discussed in this book and their corresponding temporal sensations.

2It is obvious that loudness depends on the sound pressure level (SPL).

3X: Note that factors of φ1 and τe are mutually related. It is note worthy that temporal sensations are associated with the left hemisphere, so that temporal sensations may be affected by two temporal factors of the sound field: t1 and Tsub in addition. For example, Sayles and Winter (2008) have shown that pitch is influenced by the reverberant energy ratio equivalent to the value A (Equation 3.2), which depend on the distance between the sound source and a receiving position.

this, then we must also take spatial factors extracted from the interaural correlation function IACF into consideration. In fact, timbre of the sound field that we investigated using dissimilarity judgments (Section 6.6) may be described as a function of both temporal and spatial factors. In this table, a capital letter X signifies the most important factor(s) for describing a given sensation. A small x indicates a dependent factor that may warrant special attention. Some factors interact – factors φ1 and τe are to some extent related to each other. The factor D signifies the physical duration of the sound signal. Because of temporal summation, the perception of loudness should be described in relation to sound duration D together with other temporal factors. Pitch has been described in terms of the ACF factor τ1 (fundamental frequency F0 = 1/τ1), and its perceived strength is given by its relative amplitude φ1.

16.1.2 Auditory Spatial Sensations

Table 16.2 presents an overview of auditory spatial sensations including the apparent source width ASW, subjective diffuseness and sound source localization. Localization in the horizontal plane, for example, is well described in terms of spatial factors extracted from the interaural correlation function IACF. Localization in the median plane, however, does not necessarily involve the binaural representation (if only because the IACF is little changed by elevation) and can be described in terms of temporal factors extracted from the monaural autocorrelation function ACF alone (Session 7.1.2).

The apparent source width ASW of band-pass filtered noise has been given by Equation (7.4). We have little data on effects of τIACC on this sensation, which might be added to the expression. However, as far as acoustic design of concert halls is concerned, listening level LL is usually governed by the power watt level PWL of the sound source in a room, a parameter that musicians can control. But,

Table 16.2 Auditory spatial sensations in relation to the factor extracted from the IACF

1LL = 10 log [ (0)/ (0)reference], where (0) = [ ll(0) rr(0)]1/2.

2X: Major factors to describe corresponding spatial sensations. (The related section is indicated

in the parentheses.)

3 Factors to be examined whether or not they influence the respective sensation. Note that factors for localization in the median plane may be extracted from the ACF as discussed in Section 7.1.2 (Sato et al., 2001).

at the design stage of the sound field in a concert all, all we can do is calculate the distribution of relative sound pressure level in an enclosure. The condition of τIACC ≈ 0 is usually realized in a room by producing the strongest direct sound. The ASW for multiband complex noise is given by Equation (7.5). It is worth noting that WIACC depends mainly on the frequency composition of a sound signal. If the sound signal contains only low frequencies, then the value of WIACC is large and the ASW becomes wide.

Finally, subjective diffuseness has been well expressed by Equation (7.6). It is interesting that the power of IACC is commonly β ≈ 3/2 as expressed by Equations (7.4) through (7.6), and the power of WIACC in Equations (7.4) and (7.5) is 1/2.

16.1.3 Auditory Subjective Preferences

Table 16.3 reviews the most significant factors for describing subjective preference, reverberance and speech intelligibility as an overall subjective response to a sound field. They are related to temporal factors extracted from the ACF of the source signal, spatial factors extracted from the IACF, and additional orthogonal factors of first reflection time t1 and subsequent reverberations Tsub of the sound field. Table 16.4 lists cerebral hemisphere dominance in relation to the temporal and spa-

Table 16.3 Subjective preference of the sound field in relation to the factors extracted from both the ACF and IACF, as well as orthogonal factors of the sound field

1 X: Major factors to describe corresponding subjective attributes. (The related section is indicated in the parentheses.)

2LL = 10 log [ (0)/ (0)reference], where (0) = [ ll(0) rr(0)]1/2.

3The preferred condition is obtained under the condition of τIACC = 0.

4Factors to be examined whether or not they influence the respective response.

Table 16.4 Hemispheric specializations of temporal and spatial factors observed by analyses of the AEPs, EEG, and MEG

1Sound source used in experiments is indicated in the parentheses.

2The flow of EEG alpha wave from the right hemisphere to the left hemisphere for music stimulus in change of the IACC was determined by the CCF |φ(τ)|max between alpha waves recorded at different electrodes.

3Soeta and Nakagawa (2006).

4Palomaki et al. (2002).

tial factors of the sound field, and Table 16.5 shows hemispheric activities related to subjective preference of the sound field. In the preferred conditions for a wide variety of sensations, alpha rhythms persist more coherently over longer durations (larger values of τe) and over wider areas of the brain.

The most preferred conditions of the four orthogonal factors of the sound field are described in Section 3.2. As is expressed by Equation (3.9), the remarkable finding is that both temporal and spatial factors xi (i =1,2,3) are commonly expressed in terms of the 3/2 power of the factor normalized by its most preferred value. But, as far as the IACC is concerned (i = 4), it is expressed in terms of the 3/2 power of its “real value” indicating that it provides the greatest contribution of the orthogonal factors. Dissimilar signals arriving at two ears, that indicate a small value of the IACC, are almost invariably the preferred condition without exception.

16.1.4 Effects of Noise on Tasks and Annoyance

Table 16.6 summarizes the effects of noise on the performance of different mental tasks and the contributions of temporal and spatial factors to annoyance. Effects of noise on left hemisphere intensive tasks such as adding numbers may be described in terms of temporal factors extracted from the ACF of the noise stimulus. This can

Table 16.6 Effects of noise on mental tasks and annoyance in relation to temporal and spatial factors extracted from the ACF and the IACF, respectively

1Symbol of “Var” represents the variance defined by σ2 = 1/n (xi – m)2, xi: the value of data i; m: the mean value, and n: the number of the data.

2X: Major factors, which have well described respective subjective attributes in this book.

3X: Note that factors of signal regularity or periodicity strength φ1 and effective duration τe are mutually related.

4–: Factors to be examined in the future, whether or not they influence on respective subjective attributes.

D: Physical duration of the sound signal.

5LL = 10 log [ (0)/ (0)reference], where (0) = [ ll(0) rr(0)]1/2.

6SPL was measured at one of two ear entrances or by a single microphone at the center of the

head.

7In this context, one might hypothesize that music is associated with the left hemispheric factors more than the right hemispheric factors, and noise is associated with the right hemispheric factors more than left hemispheric factors. However, further investigations on hemispheric specialization for single factors, for example, τ1 and φ1 are needed.

be considered as an interference effect in the left hemisphere. On the other hand, effects of noise on the right hemisphere intensive tasks such as pattern searches might be described in terms of spatial factors extracted from the IACF of the noise field and analogously as interference effects in the right hemisphere.

When spatial factors (IACC and SPL) of noise fluctuate, then these spatial factors become significant as generators of annoyance (Equation (11.3)). And, when τIACC and SPL fluctuate, annoyance is expressed by Equation (11.5). In the more general example of evaluating the annoyance of traffic noise, fluctuations of parameters should be investigated in relation to both the temporal and the spatial factors of the noise field. In fact, a linear combination of the three variables (Var_SPL, τe, Var_τ1) as approximately expressed by Equation (11.1) has been used to effectively predict the scale value of annoyance of traffic noise.