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Title

Study on blind estimation of Speech Transmission
Index in room acoustics

Author(s)Ikeda, Tomohiro; Unoki, Masashi; Akagi, Masato

Citation

2011 International Workshop on Nonlinear
Circuits, Communication and Signal Processing(NCSP'11): 235‑238

Issue Date

2011‑03‑02

Type

Conference Paper

Text version

publisher

URL

http://hdl.handle.net/10119/9974

RightsThis material is posted here with permission of
the Research Institute of Signal Processing
Japan. Tomohiro Ikeda, Masashi Unoki, and Masato
Akagi, 2011 International Workshop on Nonlinear
Circuits, Communication and Signal Processing(NCSP'11), 2011, pp.235‑238.

Description

Japan Advanced Institute of Science and Technology

2011 International Workshop on Nonlinear Circuits,
Communication and Signal Processing
NCSP'11, Tianjin, China, March 1-3, 2011

Study on blind estimation of Speech Transmission Index in room acoustics
Tomohiro Ikeda, Masashi Unoki, and Masato Akagi
School of Information Science, Japan Advanced Institute of Science and Technology
1-1 Asahidai, Nomi, Ishikawa, 923-1292, JAPAN
Email: {kiiroitori3, unoki, akagi}@jaist.ac.jp

Abstract1
TR = 0.1 s

0.9
0.8
0.7

MTF, m(fm)Speech transmission index (STI) is one of the objective measurements that assess speech transmission quality in the room
acoustics. This paper proposed a method for blindly estimating STI based on the concept of the modulation transfer function (MTF). In this method, STI can be estimatedfrom the estimated MTFs in the seven octave-bands, by using
our previous method for blindy estimating reverberation time
(RT). Simulations were carried out to evaluate the proposed
method, in realistic environments (SMILE2004 datasets). Results showed that the proposed method can effectively estimate both RT and STI from these reverberant environments.

TR = 0.3 s

0.6
0.5
0.402

R

0.3
T =1s
R

0.2

T =2s
R

0.1
0
0

5

1. Introduction
Evaluations for speech transmission quality are requiredfor designing the desired room acoustics. Therefore, the objective indexes or measurements are needed for assessing the
speech quality and intelligibility. Thus, some indexes suchas the articulation index (AI) and the contribution degree of
early reflections have been used to assess speech transmission
quality. These indexes, however, cannot be used to assessthem in both reverberant and noisy environments. Speechtransmission index (STI) is the typical index that can assess
the speech transmission quality in these environments [1].
Currently, method for calculating the STI [2] has been standardized by IEC 60268-16 [3]. This method is based on theconcept of the modulation transfer function (MTF) that was
proposed by Houtgast and Steeneken [4]. This concept aims
to account for relationship between the transfer function in an
enclosure in terms of input and output signal envelopes andthe characteristics of the enclosure such as reverberation. STI
is derived from the weighted summation of the MTFs in theseven sub-bands (octave-bandwidths) of the room impulse response (RIR) [5]. Therefore, measurement of the MTF is an
important key point to calculate the STI.
There are two methods for measuring the MTF [6]. One
is to measure the MTF from the RIR. Another is to directly
measure modulation distortions in the room acoustics using
100% AM-signals. However, these methods must be used in
actual measurements. Therefore, it is difficult to obtain the

T = 0.5 s

0.4

10Modulation frequency, fm [Hz]15

20

Figure 1: Theoretical curves presenting MTF, m(f m ), undervarious conditions with T R = 0.1, 0.3, 0.5, 1.0, and 2.0 s.
STI by using these methods in any sound environments inwhich people cannot be excluded from these environments.
Previously, method of blindly estimating reverberation
time (RT) have been proposed by our research group [7] forvarious signal processing. This method is based on the MTF
concept and thus estimates the RT from the observed signals
without measuring the RIRs. This paper aims to propose ablind estimation of the STI using the same approach we used.
2. MTF concept
The MTF concept was proposed by Houtgast andSteeneken to account for the relationship between modulation index of the power envelope of input and output signals
and characteristics of the room. This relationship is defined ascharacteristics between the temporal power envelope of input
and output signals. This is also defined as follows:
Input Ii2 (1 + cos(2πfm t))
OutputIo2 {1 + m(fm ) cos(2πfm (t − τ ))}

(1)
(2)

where Ii2 and Io2 represent the magnitude of the input and output signals. Here, f m represents the modulation frequency- 235 -

125 Hz#1

Table 1: Relationship between STI and speech quality.
STI
Quality

0.0 ∼ 0.45
Bad

0.45 ∼ 0.6
Fair

0.6 ∼ 0.75
Good

0.75 ∼ 1.0
Excellent

250 Hz500 HzRoom impulse
response (RIR)and τ represents the initial phase. m(f m ) represents modulation index, that is the MTF.
The observed reverberant signal, the original signal, andthe stochastic idealized RMR are assumed to correspond toy(t), x(t), and h(t). The signal is also assumed to compose of
temporal envelope, e(t), and noise carrier, c(t). By assuming
linear systems and the mutual independence between carriers,in this definition, e 2y (t) can be represented ase2y (t) = e2x (t) ∗ e2h (t).
From Eqs. (1) - (3), they are represented as follows:e2x (t)e2y (t)= e2x (1 + cos(2πfm t))=

e2x{1 + m(fm ) cos(2πfm t)}
α

h(t)

h1(t)

MTF
calculation

h2(t)

MTF
calculation m2(fm)

h3(t)

MTF
calculation m3(fm)#2#3Octave-band#4filterbank 1 kHz
h4(t)
#5
2 kHz

h5(t)
h6(t)

MTF
calculationm6(fm)h7(t)MTF
calculationm7(fm)#78 kHz

m4(fm)

MTF
calculation m5(fm)

#6
4 kHz

MTF
calculationm1(fm)

STI
calculation

Calculated
STI

Figure 2: Block diagram for calculating STI.

(ii) Calculating SNRs from the MTFs: SNRs, N (k, i), are(3) calculated from MTF, m (F ). In the case of Eq. (6), m (F )kiki
and N (k, i) are represented as follows:
(4)

mk (Fi )(5)=2 (−1/2)
TR
1 + 2πFi
13.8

N (k, i) = 10 log10 mk (Fi )/(1 − mk (Fi ))

(8)
(9)

Here, the stochastic idealized RIR (Schroeder’s RIR [6]),h(t), is represented as follows:
h(t) = eh (t)ch (t) = aexp(−6.9t/TR )ch (t)From these, the MTF is represented as follows:  2 (−1/2)β TRm(fm ) =   = 1 + 2πfm
α13.8(iii) Calculating transmission indexes (TIs): TIs, T (k, i),are calculated by normalizing the SNRs, N (k, i), as follows:⎧(6)(15 < N (k, i))⎨ 1
N (k,i)+15
T (k, i) =
(10)
(−15
≤ N (k, i) ≤ 15)
30⎩
0(N (k, i) < −15)

(7) (iv) Calculating modulation transmission indexes (MTIs):
MTIs, M (k), are calculated by averaging TIs, T (k, i), in eachoctave-band as follows:∞ 2
where α and β are represented as α = 0 h (t)dt and β =
14
∞ 2
1
h (t) exp(−jωm t)dt. Here ,TR is a parameter of RT.
0
M (k) =T (k, i)(11)14 i=1Figure 1 shows the MTF, m(f m ), as a function of T R . The
MTF has characteristics of low-pass filtering as a function of
fm . Here, when T R is 0.5 s, m(fm ) is 0.402 at fm = 10 Hz. (v) Calculating STI: Finally, STI is calculated as theThis means that the modulation index of the input is reduced weighted summation as follows.
to be 0.402 due to reverberation.
7
STI =3. Calculation of STI

W (k)M (k)

(12)

k=1

Method for calculating the STI is standardized by IEC
60268-16 [3]. Table 1 shows the correspondence between the
STI and their quality to assess speech transmission quality inthe room acoustics. Figure 2 shows block diagram for calculating STI. Calculation process of the STI can be summarized
as the following steps.
(i) Calculating MTFs in the seven octave-bands: MTFs,
mk (Fi ), are measured in the seven octave-bands (the center frequencies in these bands are from 125 Hz to 8 kHz,k = 1, 2, 3, · · · , 7). This has the fourteen modulation frequencies (the center frequencies in fourteen one-third octavebands are from 0.63 Hz to 12.5 Hz, i = 1, 2, 3, · · · , 14).

Here, the contribution rates, W (k), are determined as
W (1) = 0.129, W (2) = 0.143, W (3) = W (4) = 0.114,
W (5) = 0.186, W (6) = 0.171, and W (7) = 0.143.
4. Blind estimation of STI
This section explains how to blindly estimate the STI basedon the MTF concept. Figure 3 shows block diagram for estimating the STI from the observed reverberant signals.
First, the observed signal (reverberant signal) is decomposed into the seven sub-band components by using theoctave-band filterbank whose the center frequencies are from- 236 -

MTF
estimationm2(fm)y3(t)MTF
estimationm3(fm)

Octave-band#4filterbank 1 kHz
y4(t)

MTF
estimation

#3

#5
2 kHz

y5(t)
#6

4 kHz

m5(fm)y6(t)m6(fm)y7(t)MTF
estimationm7(fm)

−10
−15
−20
−25
−30

125 Hz to 8 kHz (k = 1, 2, 3, · · · , 7). Second, the MTF
in each octave-band is estimated from the corresponded observed sub-band signal by using the blind RT-estimation
method [7]. Finally, the algorithm described in Sec. 3 is used
to estimate the STI from the estimated MTFs.
In this section, we explain clearly an important keyconcept of the proposed method. Figure 4 shows relationshipbetween the modulation spectra of the input and output signals. The dashed curve in Fig. 4 is the MTF at T R = 2.0.
The modulation spectrum of the input has a peak of 1 (or 0dB) at the dominant modulation frequency of f m = 5 Hz.
Here, there are the three characteristics: (1) The MTF at 0 Hz
is 0 dB. (2) The original modulation spectrum at f m = 5 Hz
is the same as that at 0 Hz. (3) The entire modulation spectrum of the reverberant signal is reduced as the RT increases,
according to the MTF.
These useful characteristics enabled us to model a strategy
for blindly estimating the RT from the observed signal. This
meant that a specific RT could be determined by compensating for the reduced modulation spectrum at a dominant f m(fm = 5 Hz in Fig. 4) based on the MTF being 0 dB (m(f m )was restored to 1). Thus, we obtained
Ex (0) = Ey (0),Ex (0) = Ex (fd )(13)where Ex (fm ) is the modulation spectrum of e 2x (t) andEy (fm ) is that of e2y (t). fd is the dominant modulation frequency. Based on these equations, we obtained:m(fd ) = Ey (fd )/Ex (fd ) = Ey (fd )/Ey (0)Modulation spectrum (Output)

0

5

10

5
0
−5
−10
−15
−20
−25
−30

0

5

10

Modulation frequency [Hz]Figure 4: Hints of estimating MTF

Figure 3: Block diagram for blindly estimating STI.

Ex (fd ) = Ey (0)0−5Modulation frequency [Hz]MTF
estimation

#7
8 kHz

MTF
estimationm4(fm)

STI
calculation

Estimated
STI

5

Normalized power [dB]

y2(t)

#2

Normalized power [dB]m1(fm)

500 Hzy(t)Modulation spectrum (Input)

MTF
estimation

250 HzReverberant
signal#1y1(t)125 Hz(14)

Therefore, if the dominant modulation frequency, f d , of theobserved signal can be detected, the reverberation time, T R ,and MTF, m(fm ), can be estimated by using Eq. (14).

generated by convolving AM-noise signal with realistic RIRs.
Modulation frequency is 5 Hz. We used 43 RIRs in these simulations, produced in SMILE2004 datasets [8]. Table 2 shows
the RIRs information in these simulations (MPH: Multi Purpose Hall, CCH: Classic Concert Hall, GSH: General SpeechHall, RB: Reflection Board, AB: Absorption Board, and AC:
Absorption Curtain).
Figure 5 shows the estimated STIs. Horizontal axis indicates the directly calculated STIs from the RIRs and verticalaxis indicates the estimated STIs using the proposed method.
The numerical values in Fig. 5 are corresponded to the ID
number of RIRs in Tab. 2. The dotted-line (diagonal line) in
Fig. 5 shows ideal estimated value of the STI. Figure 6 showsthe estimated reverberation time. Horizontal axis indicatesthe reverberation times described in Tab. 2. Vertical axis indicates the corresponding estimated RT which are averaged
from the estimated RTs in the seven octave-bands using the
proposed method. The numerical values in Fig. 6 are corresponded to the ID numbers of the RIRs in Tab. 2.
Figure 5 shows that most of the estimated STIs are locatedon the ideal line and the others are almost close to the line.
This means that the proposed method can effectively estimate the STI from the observed reverberant signals. On theother hand, Figure 6 that the corresponding estimated T R are
not located on the ideal line and the most of estimated T R stend to be under-estimation. Our previous paper [7] reported
that the degree of approximation of the power envelopes of
RIRs may have affected the accuracy of estimating T R , especially in non-exponential decay of RIRs. Fortunately, thistrend of under-estimating does not greatly affect accuracyof estimating the STI. It seems to be important for estimating the STI that the MTF represented in Eq. (7) should beclose to the measured MTF. In both figures, RMS (root-meansquared) error, calculated from the differences between calculated and estimated values, E rms , is calculated and these aresmall value in both estimating the STI and RT.

5. Evaluation

6. Conclusions

We carried out evaluation simulations using the reverberant signals to confirm whether it worked on blind estimates
based on our concept. We used the reverberant signals that areThis paper proposed the method for blindly estimating the
STI, based on the MTF concept. We carried out the simulations using AM signal and the RIRs in SMILE2004 to eval-- 237 -

1

Table 2: RIRs using simulations of estimating STI blindly
RIR No.
301
302
303
304
305
306
307
308
319
321
309
310
311
312
313
314
315
316
317
323
324
325
326
201
318
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418

TR [s]
1.09
0.80
1.44
1.04
1.93
1.35
1.42
1.54
1.47
2.16
2.35
2.34
2.35
2.39
2.38
1.14
1.96
1.92
2.55
2.32
1.77
1.74
1.69
1.36
0.85
0.62
1.12
1.09
1.54
0.71
1.30
3.03
3.62
2.82
1.70
0.36
0.38
1.57
2.72
1.95
1.53
1.49
1.40

3736

0.8

26

0.7

Estimated STI

Room condition
MRH 1 (with RB)
MPH 1 (without RB)
MPH 2 (with RB)
MPH 2 (without RB)
MPH 3 (with RB)
MPH 3 (without RB)
MPH 4 (with AB)
MPH 4 (without AB)
MPH 5 (14, 000 m3 )MPH 6 (19, 000 m3 )CCH 1 (5, 600 m3 )CCH 1 (d = 6 m)
CCH 1 (d = 11 m)
CCH 1 (d = 15 m)
CCH 1 (d = 19 m)
CCH 2 (6, 100 m3 )CCH 3 (20, 000 m3 )CCH 4 (with AC)
CCH 4 (without AC)
CCH 5 (17, 000 m3 )CCH 6 (1F front)
CCH 6 (2F side)
CCH 6 (3F)
Lecture room
Theater hall (3, 900 m3 )Meeting room (130 m3 )Lecture room (400 m3 )Lecture room (2, 400 m3 )GSH (11, 000 m3 )Church 1 (1, 200 m3 )Church 2 (3, 200 m3 )Event hall 1 (28, 000 m3 )Event hall 2 (41, 000 m3 )Gym 1 (12, 000 m3 )Gym 2 (29, 000 m3 )Living room (110 m3 )Movie theater (560 m3 )Atrium (4, 000 m3 )Tunnel (5, 900 m3 )Concourse in train station
GSH 2 (1F front)
GSH 2 (1F center)
GSH 2 (1F balcony)

25
9 16
43
61
1040
18
41
21
22
29
33
31
32 17
2335
1938
39
14 42
20
5
4
34
12
15
13
11
3

0.6
0.5
0.4

27
30
728
8
2 24

0.3
Erms = 0.043054

0.2
0.1
0
0

0.2

0.4

0.6

0.8

1

Calculated STI

Figure 5: Estimated STI from reverberant signals.
4
ideal line
3.5

Estimated reverberation time [s]ID No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

ideal line
0.9

3
5

2.5

15
12

4

20 19
14
39

2
4238 35
23

1.5
1

225
30

0.5

17
31 29 22
21 18
40
43 41
10
624 8
1
28
16 79
27

33

32

Erms = 1.1818

26
36
37

0
0

0.5

1

1.5

2

2.5

3

3.5

4

Reverberation time [s]Figure 6: Estimated RT, TR , from reverberant signals.

uate the proposed method. Results showed that the proposed
method can effectively estimate the STIs as well as RTs fromthe reverberant signals.
In our future work, we will reconsider an optimal estimation of the MTF and T R and test their blind estimation in thecase of reverberant speech signals.
References[1] Toida, Y. “Speech intelligibility in sound fields,” J. Acoust.
Soc. Jpn., 51(4), 312–316, 1995.
[2] Sato, H., Morimoto, M., and Sato, H. “Evaluation of speechtransmission performance using listening difficulty ratings,” J.
Acoust. Soc. Jpn., 63(5), 275–280, 2007.

jective rating of speech intelligibility by speech transmission
index.
[4] Houtgast, T. and Steeneken, H. J. M., “The Modulation Transfer Function in Room Acoustics as a Predictor of Speech Intelligibility,” Acustica., 28, 66–73, 1973.
[5] Steeneken, H. J. M. and Houtgast, T., “A physical method formeasuring speech-transmission quality,” J. Acoust. Soc. Am.,67, 318–326, 1980.
[6] Schroeder, M. R., “Modulation Transfer Function: Definition
and Measurement,” Acustica, 49, 179–182, 1981.
[7] Unoki, M. and Hiramatsu, S. “MTF-based method of blind estimation of reverberation time in room acoustics,” Proc. EUSIPCO2008, Lausanne, Switzerland, CDROM, 2008.
[8] Architectural Lnstitute of Japan, “Sound library of architectureand environment, Gihodo Shuppan Co.”, Ltd., Tokyo, 2004.

[3] IEC 60268-16:2003. Sound system equipment - Part 16: Ob-- 238 -