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The Binaural Signal From a Symphony Orchestra
Magne Skalevik
To cite this version:
THE BINAURAL SIGNAL FROM SYMPHONY ORCHESTRAS
Magne Skålevik
1,21AKUTEK www.akutek.info,
Bølstadtunet 7, 3430 Spikkestad, Norwayy
2Brekke & Strand, Oslo, Norway
msk@brekkestrand.no
ABSTRACT
When listening to a live performance with a symphony orchestra, perceptual aspects like localization, source broadening and envelopment are depending on properties of the binaural signal at the listener's ears, and the Inter-Aural Cross-Correlation (IACC) in particular. It is assumed that these aspects can enhance engagement and excitement in the listener. In order to gain more insight, the binaural signal at a listener’s ears has been recorded during concerts with symphony orchestras in several concert halls in Europe and United States. An IACC(t) signal in the range [-1,1], in octave bands 125-4000Hz, was computed from the sequence of IACC in 100ms windows. Higher values, up to 0.80-1.0, are associated with point-like sound images, while wider sound images are perceived when values are 0.50-0.80. Mean values of
IACC varies far more from part to part during a
symphony than from one hall to another. Typically, solo parts have higher IACC, while string section and tutti parts have lower IACC than the average part. The former is perceived as point-like, while the latter is perceived as wide sound images. Fluctuations in the IACC(t) signal was a characteristic feature throughout, created from fluctuating source radiation combined with fluctuations in the reverberant sound field. While the fluctuations make data very complicated to interpret, they seem to be the very basis for the perceived parallel streams of Localization, Envelopment and Source Broadening reported in literature. So-called acoustical glimpsing suggests an explanation as to how an instrument can be perceptually wide, enveloped by reverberant sound, and still being localized as a point. Examples of characteristic
IACC spectra from various instruments and groups, and
statistics from binaural data of total duration 87560 seconds are presented and discussed.
1. INTRODUCTION
While inter-aural cross-correlation (IACC) as a metric in audio, binaural hearing and localization is well known[1], this author has yet to find systematic measurements and analysis by other authors where this metric is used to describe and understand the binaural signal at the ears of an audience member listening to symphony orchestra performances in concert halls. With this background, this author launched the Binaural Project[2] in 2011, and has previously presented three papers on the subject, in 2015[3], 2016[4], and 2017[5]. The present paper is the
latest report from the progress of the project. Chapter 2 describes technicalities. Chapter 3 describes perceptual effects and listener aspects related to IACC. Chapter 4 presents examples of features in IACC -data during concerts with symphony orchestras. Chapter 5 presents statistics from 87 sessions and 17 halls, a total of 87560 seconds of binaural data. Final comments are given in Chapter 6.
2. INTER-AURAL CROSS-CORRELATION 2.1 Cross-correlation, IACC and the expected impact from the direct-to-reverberant energy balance.
Cross-correlation is a mathematical function with many applications and interpretations. In general, it is used as a measure of common features in a data sequence pair of equal length. In stereo audio, the left and right signal is such a sequence pair, and the cross-correlation of a stereo signal would be a measure of the amount of common signal content being present in both channels, i.e. the left and right channels. In live concert listening, the left and right signals would be reflected (reverberant) sound at the two ears, and the common signal would be the direct sound component from a musical instrument upfront.
2.2 Data collection
Binaural signals were recorded while listening to symphony orchestras in various concert halls during public performance, using tiny microphones in the ear canal according to the procedure in the Binaural Project description[2]. All the binaural signals forming the raw data in the investigation reported in this paper have been recorded during the years 2012-2019 with the one and same pair of in-ear-microphones from Sound Professionals, H2 Zoom wave-recorder, at 16-bit rate, 128 bit/s, sampling frequency 44.1kHz, and stored in the common wave-format with file extension *.wav. Equipment and measurement arrangement is illustrated in Figure 1.
2.3 Signal processing and post-processing of data
This section explains how the binaural signals with sampling frequency 44.1kHz are converted into IACC(t) signals by calculating IACC for every 100ms window, a method used throughout the current investigation.
The algorithm used to convert the binaural signal pair from the left and right ears, to a sequence of IACC-values can in short be described as follows
x Filtering, from e binaural signal producing a set of 6 parallel signals, one for each octave band 125Hz to 4kHz
x Dividing the signals into a sequence of 100ms windows, each with 441 samples
x From each 100ms window and each octave band compute the normalized cross-correlation function IACCF(i) for the 47 different lags from i=-23 samples lag, to
i=+23 samples lead1, taking values in the
range [-1.0,1.0]
o Inter-aural coherence IC=IACCF(0), is the special case i=0, with neither lead or lag, which would be the inter-aural cross-correlation from sound arriving from a source up-front, i.e. a source in the median plane; in an-echoic conditions a source in the median plane would ideally produce IC=1.0
x In the 100ms window at time t, let IACC(t,f) be the highest value of IACCF(t,f,i) with any i in the interval [-23,+23] in the octave band f,
o where t belongs to any sequence
t=t0+n·0.1s, where n=0,1,2,….,
starting at arbitrary time t0
Note that the normalization inherent of the IACCF in each 100ms window cancels out any differences between left and right ear as to biased SPL in the sound field or any gain differences in the measurement chain.
2.4 IACCF and source direction
This section explains how inter-aural cross-correlation function IACCF(i) can be used to determine the direction to the most prominent sound source, and to measure how strong this sound is relative to other sounds, e.g. diffuse reverberant sound.
Mathematically, IACCF(i) is a function of sample-lags i, where i is the number of samples the signal at the right ear is shifted (lagged) relative to the signal at the left ear. With a point source upfront, i.e. at azimuth angle Dequal to zero, IACCF(i) will take its maximum value at i=0. With other azimuth angles, its maximum will occur with i
1 23 samples lag is 0.52 ms, the delay from a 17.7cm
detour around the head. In common binaural hearing models, a signal arriving from left would arrive at the right ear with approximately 23 samples lag relative to signal arriving at the left ear. With i the number of sample lags, W=i/44.1kHz, IACC(i) converts to the
common form IACC(W).
different from zero, and there will be a one-to-one relationship between Dand the i for which the maximum of IACC(i) occurs. E.g., i=±1 indicates a source at
D=±2.5 degrees. Up to 30 degrees, angle increments are
approximately 2.5 degrees for each sample increment. For bigger azimuth angles than 30 degrees, our localization ability gets gradually less precise, and from
i=22 to i=23, the corresponding azimuth angle increases
from 70 to 80 degrees. With this relationship IACCF(D)
becomes a function of azimuth angle. By letting
IACCF3(D) be average IACCF from the 3 band-filtered
binaural signals 500, 1000 and 2000Hz, an accurate localization tool is obtained. Figure 2 presents
IACCF3(D) from 7 occasions of an oboe giving the
sustained a’ note during tuning of symphony orchestras in 5 concert halls: Stavanger Concert Hall, Geffen (AKA Avery Fisher) Hall, New York (NY), Berlin Philharmonie, Helsinki Music Centre and Paris Philharmonie.
Azimuth angles and IACCF-values at maxima varies with receiver orientation and distance relative to the source. Reverberant sound and common audience noise both have a decorrelating effect, and longer source-receiver distance will reduce the direct sound level. These factors in general contribute to lower maxima values. Reflections from floor, ceiling and other surfaces can increase correlation if they arrive along the so-called cone of
confusion, i.e. the group of reflected sound components
that each causes an ITD (inter-aural time-difference) equal to that of the direct sound. The examples in Figure 2 are all from sequences of 4410 samples, i.e. binaural signal windows of 100ms length.
Figure 2 IACCF3(D) from oboe giving a sustained a’
(440Hz) in various concert halls. Azimuth angles and IACCF3-values at maxima varies with receiver orientation and distance relative to the source. Maximum values depend on reverberant sound, audience noise, source receiver distance and single reflections.
2.5 IACC and signal filtering
In main-stream hearing models, the binaural signal is filtered into parallel 3rd octave band signals, from which
common to use a simpler analysis, and single number parameters in literature, like IACCE and IACCL are calculated from the average IACC from the three mid-frequency octave bands 500Hz, 1kHz and 2kHz, often denoted IACCE3 and IACCL3. These octave bands are chosen because they prove to be the more significant, critical and more sensitive to changes in the binaural signal, as will be demonstrated in the following sections. A different simplified model would be to calculate IACC from a band-pass filter covering the mid-frequency octaves mentioned above. Because of the level-normalizing mechanism inherent in the IACC algorithm, this model would allow stronger frequency components to be more emphasized in the single-value IACC than in the aforementioned model, where the frequency bands are weighted equally, regardless of the energy in the individual octave band. Despite this general difference, the two models will not necessarily yield very different results, as demonstrated when applied to the sound from the oboe in tuning of the orchestra in Philharmonie, Figure 3. Note that the window analyzed here is from 10s later in the tuning process, thus the “IACCF3” curve is slightly different from the one in Figure 2. In this case, the IACCF taken from the broad-band filtered signal, the “BB”-curve, forms a bit narrower and taller shape.
Figure 3 Two simplified hearing models applied to an oboe tone during tuning in Paris Philharmonie, one (IACCF3) based on average cross-correlation from 3 parallel filtered signals in 500Hz, 1kHz and 2kHz octave bands, and another (BB) based on a single broad-band filtered signal.
3. TYPICAL IACC VALUES AND PERCEPTUAL EFFECTS
3.1 IACC and listening aspects
Figure 4 presents typical listening aspects during a symphony orchestra concert and their typical corresponding values on the IACC scale. As will be demonstrated in this paper, music instruments playing in a concert hall do not produce a constant IACC value. A solo oboe can, within any second, fluctuate more or less over the whole scale between 0.1 and 0.9 in the 500-4000Hz region. The fluctuations allow brief glimpses of all the four listening aspects in the diagram, happening so
fast that they are not perceived as discrete events, but rather form parallel streams of localization, source broadening and envelopment. And there are no sharp borders between them. Importantly, it even occurs during sustained notes, meaning that impulse-like components in the sound is not necessary.
For reference, since they would be known from literature,
IACC from early parts and late parts of impulse response
measurements in classical ballroom type concert halls are included in the diagram, denoted IACCE and IACCL, respectively. IACCL represents a low limit for what can be expected in a diffuse, reverberant field with no direct sound present.
3.2 Frequency regions
Note that the low-frequency region LF, distinguishes from the rest of the spectrum. Because of the limited size of the human head, there is little acoustical separation between the left and the right ear, so IACC in the LF-region would be close to 1 even in a diffuse reverberant sound field. The significance to binaural perception in this region is not well established and will not be discussed in this paper.
In the octave bands 500-4000Hz, where the human head forms a screen between the two ears, the brain will find available information about directions of incoming sound. Above 1500Hz, ques from differences in intensity level are increasingly important. IACC is particularly sensitive changes in the sound filed in the mid-frequency (MF) octaves 500Hz and 1kHz. From measurements of IACCE and IACCL it has been common practice to present single-number values from the three middle octaves
500Hz, 1kHz and 2kHz.
3.3 IACC and the direct-to-reverberant energy ratio
If direct sound energy is d and reverberant energy is r, the to-reverberant ratio is d/r and the direct-reverberant balance is D-R=10*log(d/r). As a rule-of-thumb, in the MF-HF-region, IACC will vary roughly between 1 and 0 as d/r varies between 1 and 0. However, for a given d/r, IACC can be lower if lateral reflections are strong, and higher if vertical or other reflections in the median plane are strong.
At a concert listeners ears, d/r will fluctuate, due to stochastic processes explained elsewhere in this paper, around an average largely determined by source-receiver distance and source directivity, and consequently, so will
IACC.
4. EXAMPLES OF IACC FROM SYMPHONY ORCHESTRAS IN CONCERT HALLS 4.1 Tchaikovsky 4th, Movement II
In Figure 5, IACC(t) in 100ms windows in octaves 500,
1000 and 2000Hz are plotted over time between 1080s
and 1170s during Tchaikovsky’s 4th Symphony[6], beginning of 2nd movement Andantino, performed by St. Petersburg State Academy, in Stavanger Concert Hall 25thSeptember 2012. The period 1080-1125s, the left half
of the diagram, is an oboe solo, while the right part 1125-1170s is the same melody repeated by the cello section. The continuous curve is the running average of the 3 octaves during 1 second, with an abrupt shift in IACC, indicating a big perceptual difference between the two parts.
Figure 5 Dots are IACC in 100ms bins in the octaves
500Hz, 1000Hz and 2000Hz and their running average
over 1 second (continuous curve). First half is an oboe solo (see text); second half is the cello section repeating the oboe melody. Tchaikovski 4th II in Stavanger
Concert Hall.
4.1.1 Oboe solo
During the oboe solo, IACC fluctuate around an average in the 0.5-0.6 range, with brief instants below zero and up to 0.98, upper quartile around 0.7 and lower quartile around 0.4. This means that 25% of the instants have values in the 0.7-1.0 range, corresponding to strong cues of Localization, and 25% of the instants in the 0.0-0.4 range, with ques of envelopment. The major 50% of the instants would be fluctuating in the 0.4-0.7 range, indicating a generous source broadening. In Figure 6 the statistical distribution of IACC during the oboe solo part
over 6 octave bands is presented, together with “benchmarks”, i.e. typical IACCE and IACCL from classical, rectangular concert halls.
Figure 6 Statistics from the oboe solo part in Figure 12, solid curves are average IACC from the period 1080s-1125s over the octave bands 125-4000Hz, shaded area
defines the standard deviation, and dotted curves the references for IACCE and IACCL.
4.1.2 Cello section
To the right, after 1125s, when the cello section repeats the melody presented by the oboe solo, a more compact distribution around 0.3, a much lower average, is observed. This indicates a much broader sound image, as can expected from a distributed, broader source like the cello section is. Still, as many as 40 dots (500Hz) above 0.70 can be counted between 1140 and 1170s, i.e. on average one per second, being brief instants of point-like localization, as if the individual instruments have fluctuating directivity. In optical analogy, the cellos are sparkling. The statistical distribution of IACC in the cello section part is in Figure 7.
Figure 7 Statistics from the cello section part in Figure 12, solid curves are average IACC from the period 1125s-1170s over the octave bands 125-4000Hz, shaded
4.2 Same symphony, different hall, different orchestra
For comparison of two halls, Figure 8 is similar to Figure 5, with the same symphony, but in a different hall and a different orchestra: Chicago Orchestra Hall and the resident orchestra conducted by Richardo Muti on 30th
September 2014. From the first glance, the features in Chicago are quite like those in Stavanger. However, in Chicago the oboe solo is on average IACC3=0.59 and the cellos at 0.39, while 0.54 and 0.32 in Stavanger. Not much of a difference in numbers, but the difference is audible. Another difference is the generally higher IACC in 500Hz, meaning that this octave contributes more to localization, in Chicago in both oboe solo and cello section.
Figure 8 Dots are IACC in 100ms windows in the octaves 500Hz, 1000Hz and 2000Hz and their running average over 1 second (continuous curve). First half is an oboe solo (see text); second half is the cello section repeating the oboe melody. Tchaikovski 4th II in
Chicago Orchestra Hall.
Figure 9 Statistics from the oboe solo part in Figure 8, solid curves are average IACC from the period 1195s-1237s over the octave bands 125-4000Hz, shaded area defines the standard deviation, and dotted curves the references for IACCE and IACCL.
Figure 10 Statistics from the cello section part in Figure 8, solid curves are average IACC from the period 1237s-1277s over the octave bands 125-4000Hz, shaded area defines the standard deviation, and dotted curves the references for IACCE and IACCL.
4.3 Sustained tones versus impulse
Worth noting - Figure 6 and Figure 9 shows that a quasi-stationary point source like the oboe, playing tones of duration 400-500ms, on average produces higher IACC than the early (80ms) part of an impulse in a classical concert hall, i.e. the IACCE benchmark, in the octave bands 500Hz, 1000Hz and 2000Hz.
Examples of IACCF(a) sustained a’440Hz oboe tones in various halls are shown in Figure 2.
Figure 11 demonstrates that while IACC from a sustained oboe note is much higher than IACCE in the mid-frequency bands, the IACC spectrum from sustained notes of the string and wind groups (“other”) is quite like the IACCE spectrum. The differences between solo instruments and groups will be further demonstrated below.
Figure 11 IACC from the oboe a’ 440Hz note, and average from the other instruments following, during tuning of the orchestra prior to concert in Paris Philharmonie.
4.4 IACC in melodic parts
During the oboe solo the dots are scattered within the
0.1-0.9 interval while the running 1.0s-average fluctuates
mainly in the 0.5-0.6 interval. The many dots in the
0.6-0.9 range indicate frequent perceptions, i.e. glimpses, of
the point-like source that a solo oboe ideally is. Those closer to 0.9 represent a sharper localization, while those closer to 0.6 represent a bigger aura around the oboe, i.e. bigger apparent source width. Compare this with Figure 2, where all oboe tuning-tones have their IACCF(D)
In contrast, from the cello section, dots appear more concentrated around a running 1.0s-average that fluctuates between 0.2 and 0.4, i.e. a far lower level than the oboe solo.
Figure 12: IACC(t), averages from 500Hz, 1000Hz and
2000Hz plotted over time between 1080s and 1170s
during Tchaikovsky’s 4th Symphony in Stavanger
Concert Hall, beginning of 2nd movement Andantino.
1080s to 1125s is an oboe solo, while 1125s to 1170 is the same melody repeated by the cello section; Dots are
IACC in 100ms windows and continuous curve is their
running average over 1 second. Statistics in octave bands are shown in Figure 6 for the oboe solo and in Figure 7 for the cello section part.
Figure 13 Like Figure 12, only in Orchestra Hall Chicago, performed by the resident orchestra.
4.5 IACC from various instruments, group size and playing style
Figure 14 offers a comparison of IACC average spectra from 5 parts of various length, instrumentation and playing styles from Tchaikovsky’s 4thSymphony during
a concert in Stavanger Concert Hall. Average IACCA-and IACCL-spectra from classical ballroom halls are included for reference. Figure 15 presents the exact same parts only performed by a different orchestra in Chicago Orchestra Hall. These are examples of typical features, e.g. solo instruments playing sustained notes (tones) exhibit higher IACC than groups. The violin section comes with the lowest spectra, in bowed as well as pizzicato style. From the fanfare in the opening of the symphony, played by the full brass section, IACC is higher than from the cello section in both halls. This is to be expected from the fact that the brass instruments point into the audience with high directivity in the mid- and high-frequency range, consequently producing a higher direct-to-reverberant ratio to the listener. The generally
lower IACC in 500Hz and 1000Hz in Stavanger is due to more lateral energy in the mid-frequency region in that hall. Stavanger Concert Hall have IACCE and IACCL quite like those given as reference in the two diagrams. Apart from the string section, timpani rolls and tutti parts typically produce low IACC.
Figure 14 IACC from 5 different parts from Tchaikovsky’s 4th various instruments, group size and
playing style, during concert in Stavanger Concert Hall. Average IACCE and IACCL spectra from classical ballroom type halls are given for reference.
Figure 15, similar to Figure 14, only a different orchestra and a different hall: Chicago Orchestra Hall.
5. STATISTICS FROM 87 SESSIONS IN 17 HALLS
Since the start of the Binaural Project in 2011, the author has collected data in audience position from 86 sessions during symphony orchestra performances in 17 different halls. The total duration of the analyzed binaural signals is 87560.2 seconds, equivalent to 24 hours and 18 minutes. The total number of 100ms windows analyzed is N=875602. The data size from the sessions vary with varying length of the sessions.
In Figure 16, “m(875602)” is the spectrum of average
IACC from all the 875602 windows. “s(875602)” is the
standard deviation over the windows. The mid-frequency average from octaves 500, 1000 and 2000Hz is
Figure 16 “m(875602)” is the average IACC of 875602
100ms-windows, adding up to 24+ hours of binaural
signal recorded in audience seats in 17 different concert halls during symphony orchestra performances. “s(875602)” is the standard deviation over the windows. The mid-frequency average, i.e. from octaves 500, 1000 and 2000Hz is IACC3=0.38.
The m-spectrum is basically formed by two factors, 1) the geometry of our head causing little separation at low frequencies (higher IACC below 500Hz), and 2) the decorrelation due to direct-to-reverberant ratios lower than d/r=1 in the average hall, causing lower IACC from 500Hz and upwards due to the head being an acoustical screen between the left ear and the right ear for shorter wavelengths.
The s-spectrum measures the fluctuations around the average IACC, peaking at 0.21 in 500Hz, meaning that 67% of the fluctuations are within m±0.21, i.e. in the
0.26-0.68 interval. s is partly influenced by the same
factors as “m”, but very dependent on the signal content, i.e. the music itself. E.g. an oboe solo would have bigger
s and a string section would have a smaller s.
Table 1 IACC average values in octave bands (Hz) from binaural data collected in the 17 halls. White cells hold normal values, i.e. values deviate by less than the standard deviation from the average over halls; light blue cells hold values lower than normal values (in italic); light red cells hold values higher than normal. The full names of the halls are given in Table 2.
Table 1 IACC average values in octave bands (Hz) from binaural data collected in the 17 halls. White cells hold normal values, i.e. values deviate by less than the standard deviation from the average over halls; light blue cells hold values lower than normal values (in italic); light red cells hold values higher than normal. The full names of the halls are given in Table 2.
As noted above IACC fluctuates between higher values providing “glimpses” of localization, and lower values providing moments of envelopment. These fluctuations happen so fast, they are often not perceived as separate events, but rather as parallel streams of localization and envelopment. The standard deviation measures the amount of fluctuations in IACC.
Sustained notes of enough duration and IACC-level are necessary to convey tonal clarity and to allow for localization of solo instruments, which is important for the listeners’ impression of proximity, involvement and engagement in the music being performed. The importance of duration for tonal clarity is demonstrated by the traditional oboe a’(440Hz) note in the initial tuning process, Figure 2.
Figure 17 Columns indicate the percentage of the time in which IACC average over all 6 octave bands
125-4000Hz in parts that last 1 second or more exceeds 0.50
and 0.60, respectively. For comparison the 6-octave band average of all 875602 100ms windows in this investigation is 0.51.
In order to compare the binaural quality of two concert halls, one need either the piece of music to be the same in both halls, as demonstrated in Figure 18, or a big enough amount of data for the effect of the randomness in concert program to vanish in the statistical metrics. So how can concert goers have any opinion at all about differences between halls? Well, there may be several “standard” sources included in any repertoire, like the instruments and groups in Figure 14 and Figure 15. Experienced listeners “know” for themselves how an oboe solo, a brass fanfare, a cello section, pizzicato or bowed strings do sound when binaural quality is adequate, and when it is not. The tuning process is another standard source that could be explored for its repeatability, if only people could learn to be quiet once they hear the oboe.
Figure 18 Columns indicate the percentage of the time in which IACC average over all 6 octave bands 125-4000Hz in parts that last 1 second or more exceeds 0.50 and 0.60, respectively. Comparison of pairs of halls in which the same pieces of music were played. Tchaikovsky’s 4th in Stavanger (T4-SCH) and Mussorgsky’s ‘Pictures From an Exhibition’ in Amsterdam Kupol (M-AK) and Amsterdam Concertgebouw (M-CG). The two latter were played by the same orchestra, in two consecutive days. m(87) is the average from the 87 sessions in this investigations, and thin bars in the columns indicate the variation over the 87 sessions in terms of standard deviation. The difference between SCH and COH is quite large given the fact that music is the same in both sessions, while the difference between AK and CG is small compared to the standard deviation.
6. FINAL COMMENTS
While the data collected so far indicate that there are two sources of variation in the binaural signal, 1) the music itself, and 2) differences between halls, e.g. the degree of decorrelation from lateral reverberant sound energy. Fluctuations in radiated sound power and fluctuations in directivity from the music instruments, and fluctuations in room frequency response while musical tones build up to a quasi-stationary state, combine to form big fluctuations in IACC at listeners’ ears. While the fluctuations make data very complicated to analyze, they seem to be the very reason for the perceived parallel streams of Localization, Envelopment and Source Broadening reported in literature. This interpretation of the data is very different from understanding the binaural sound from music as a composition of 1) an early energy stream described by IACCE and 2) a late energy stream described by IACCL, a concept tested by Klockgether[7]. Except for the rare cases of so-called stop-chords in orchestra music, in which the binaural quality of the reverberant tail could possibly be described by IACCL, any attempts during the Binaural Project to find BRIR-like components in the sound from a symphony orchestra has failed. Nearly all increments and decrements in the sequence of incident energy are fluctuations governed by stochastic processes and are not to be interpreted as onset and offset of direct sound. On the other hand, IACCE and
IACCL can be useful references for binaural quality of a
diffuse sound field, like in Figure 19, where further comments are given in the caption.
7. APPENDIX (THE 17 HALLS)
Table 2 List of the 17 halls and abbreviations in Table 1 AFH Avery Fisher Hall (NY)
ACG Amsterdam Concertgebouw AK Amsterdam Kupol
BGH Bergen Grieghallen BP Berlin Philharmonie BS Bodo Stormen
BSH Boston Symphony Hall COH Chicago-Orchestra Hall HEP Hamburg-Elbphilharmonie HMC Helsinki Music Centre M-NWS Miami New World Symphony
MS Milano La Scala (Concert configuration) OK Oslo Konserthuset
PP Paris Philharmonie SCH Stavanger Concert Hall SKH Stord Kulturhus TKH Tromso Kulturhus
8. REFERENCES
[1] https://en.wikipedia.org/wiki/Sound_localization
[2] https://www.akutek.info/binaural_project.htm
[3] M. Skålevik: “Can source broadening and listener envelopment be measured directly from a music performance in a concert hall?” Proceedings of the
Institute of Acoustics, IOA Auditorium Acoustics in Paris 2015.
[4] M. Skålevik: “Measurements of IACC during music performance in concert halls” Proceedings of the
International Symposium on Music and Room Acoustics, La Plata, Buenos Aires, 2016. https://www.akutek.info/Papers/MS_IACC-concert-measurements.pdf
[5] M. Skålevik: “Spatial listening aspects and the time-varying inter-aural cross-correlation during music performance in concert halls”, 24th international congress on sound and vibration, ICSV London 2017, https://www.akutek.info/Papers/MS_iacc-t_London-2017.pdf
[6] https://www.youtube.com/watch?v=cnXd4ZqN_c8
[7] S.Klockgether and S. van de Par, A Model for the Prediction of Room Acoustical Perception Based on the Just Noticeable Differences of Spatial Perception, Acta Acustica United with Acustica, 100,
