ESTIMATING THE PERFORMANCE OF SOUND RESTORATION HEARING 

PROTECTORS BY USING THE SPEECH INTELLIGIBILITY INDEX 

Amanda S. Azman 

National Institute for Occupational Safety and Health
 

Pittsburgh, Pennsylvania, USA
 

AAzman@cdc.gov
 

David S. Yantek 

National Institute for Occupational Safety and Health
 

Pittsburgh, Pennsylvania, USA
 

DYantek@cdc.gov
 

ABSTRACT 

Despite advances in engineering noise controls and 

the use of administrative controls, miners are still 

dependent on hearing protection devices for 

prevention of noise-induced hearing loss. However, 

miners often raise concerns about the audibility of 

spoken communication when wearing conventional 

hearing protectors. Electronic technologies that 

selectively process and restore sounds from outside 

of hearing protectors have been suggested as a partial 

remedy to the audibility problem. 

To assess the potential benefits of this technology for 

miners, NIOSH tested the impact of nine electronic 

sound restoration hearing protectors on speech 

intelligibility in selected mining background noises. 

Because of the number of devices and potential 

settings of those devices, it was necessary to narrow 

the choices before conducting human subject testing. 

This was done by testing the nine devices on an 
acoustic test fixture (ATF) to acquire one-third

octave-band data, and then calculating the speech 

intelligibility index (SII) to determine estimates of 

performance across device, noise and setting. The 

estimates of speech intelligibility obtained with the 

SII are highly correlated with the intelligibility of 

speech under adverse listening conditions such as 

noise, reverberation, and filtering. The results of 

fixture based testing indicate that performance varies 

little between most devices, with few showing 

exceptionally good or poor estimated speech 

intelligibility. The most significant differences in 

estimated performance using the devices were 

between the different noise sources used, regardless 

of device or setting. 

­

The findings of this research were used to select the 

devices and settings for subsequent human subject 

based speech intelligibility testing. The human 

subject testing results largely concurred with the 

findings from the acoustic test fixture testing and 

calculation of speech intelligibility index. 

Specifically, variations in background noise led to the 

greatest differences in speech intelligibility. 

INTRODUCTION 

The mining workforce experiences high levels of 

noise exposure and in turn suffers from high rates of 

noise-induced hearing loss (NIHL). The mining 

sector has the highest prevalence of hazardous 

workplace noise exposures (76%) among all 

industrial sectors [1]. Despite engineering and 

administrative controls implemented to reduce noise, 

miners report a high prevalence (24%) of hearing 

difficulty [2]. It therefore remains necessary for 

miners to use hearing protection devices (HPDs) to 

reduce the chance for acquiring NIHL. There are 

complaints, however, that HPDs have a negative 

impact on hearing some desired sounds. Specifically, 

miners have expressed concerns that wearing HPDs 

inhibits their ability to communicate with co-workers 

and reduces the audibility of alarms and other 

auditory warnings. Decreased audibility is not only a 

communication nuisance, but it can contribute to 

unsafe working conditions. For miners who exhibit 

some degree of hearing impairment, the degradation 

in audibility can be even greater. HPD manufacturers 

have recognized these issues, and they have 

developed HPDs with technology aimed to remediate 

them. 

To improve the function of the devices in 

environments where sound awareness is vital, 

electronic technology has been integrated into 

conventional hearing protectors. Several types of 

electronic hearing protectors with different intended 

purposes are available today, so an important 

distinction must be made. Electronic level-dependent, 

(also known as sound restoration) hearing protectors 

are designed to amplify some ambient sounds that are 

within a safe listening level and, by reverting to 

passive attenuation, to limit sounds that exceed the 

safe level. Active noise reduction (ANR) and impulse 

reduction electronics have also been integrated into 

conventional hearing protectors for improved 

audibility or attenuation in certain noise 

environments. This research focuses on sound 

restoration hearing protection devices (SRHPDs). 

Electronic SRHPDs have one or two microphones 

outside of the ear cup and a speaker inside so that 

ambient sound may be picked up and selectively 

transmitted to the ear. The devices are designed to 

limit, typically to 82 or 85 dB(A), sounds reaching 

the ear. Below that limit, the devices provide 

adjustable amplification to potentially improve 

audibility of sounds that are at a safe level. As 

ambient sound approaches or exceeds the limit, the 

electronic circuitry performs limiting, compression, 

or other processing to keep the sound transmitted 

inside the protector below hazardous levels. Most of 

these devices can also be worn in a passive mode by 

simply turning them off, at which point they act as a 

conventional hearing protector. Some type of control 

mechanism is accessible to the wearer of SRHPDs 

for activating the electronic processing and, in some 

cases, adjusting the gain or frequency response of the 

device. 

Previous research has examined the benefit of 

SRHPDs as compared to conventional hearing 

protectors or the open ear [3-6]. However, this 

research varies greatly in respect to methodology, 

devices tested, and subject population. This has led to 

disparity in research results. Therefore, additional 

work is needed to determine the possible benefits of 

such devices for users in mining. The aim was to 

determine whether the sound restoration technology 

provides any benefit as compared to devices 

functioning in a passive, conventional mode in 

background noises specific to those found in mining. 

Sound restoration HPDs are available from multiple 

manufacturers. At the time of this research, nine 
devices could be purchased through standard 

commercial means, all with small variations in 

product design and performance. This collection of 

devices was found through a search of hearing 

protector manufacturer’s Web sites, Internet search 

engines, and occupational safety Web sites. Although 

there may be similar devices available, they were not 

found through common search methods and therefore 

were not included in this research. To fully evaluate 

the potential benefits of this technology for 

improving audibility in underground mining, humansubject speech intelligibility testing must be 

conducted on subjects using the devices in several 

background noise conditions typical of those found in 

underground coal mining. However, because of the 

many possible combinations of device, device 

setting, and mining background noise, the choices 

must be narrowed in order to conduct subject testing 

within a reasonable time frame. This was done 

through application of the Speech Intelligibility Index 

(SII) [7]. 

The SII (ANSI S3.5-1997) is computed from the 

frequency spectrum of a specific background noise, 

estimates of speech spectrum level, and actual or 

estimated hearing threshold. The SII is highly 

correlated with speech intelligibility under adverse 

listening conditions. The SII is not equal to specific 

speech intelligibility scores; rather, it may be 

interpreted as a proportion of the total number of 

speech cues available to the listener. Through 

application of the SII equation to the speech-to-noise 

ratio in a selection of contributing frequency bands, 

the intelligibility of a communication system can be 

predicted. The type of HPDs evaluated in this study 

can be considered to represent a “communication 

system” because of its active function, which is 

designed to improved communication while in use. 

Because the interest of this study lies with speech 

intelligibility performance instead of the attenuation 

properties of SRHPDs, this type of evaluation 

provides more relevant data than standard methods 

used to test hearing protection devices such as ANSI 

S12.6-1997 (R2008) [8]. As stated within the 

standard, the SII is not intended to serve as a 

replacement for determining the speech intelligibility 

with human subjects as described in ANSI S3.2-1989 

(R 1995) [9]. Human-subject testing in accordance 

with ANSI S3.2 methodology was followed 

subsequent to use of the SII. The SII was 

implemented to reduce the possible combinations for 

subject testing by determining the SRHPDs and 

corresponding settings most likely to impact 

audibility of speech in mining noise. Additionally, 

the results of objective fixture-based testing were 

compared with subjective human-subject testing 

results to determine the accuracy of applying the SII 

for this purpose. 

METHODS AND DESIGN 

A three-stage approach was used to determine SII 

values. First, the dial settings corresponding to one 

quarter, one half, and three quarters of the maximum 

output provided by each HPD were determined. Next, 

one-third-octave band sound pressure level (SPL) 

spectra were measured at those settings with each 

device on the test fixture. Finally, the SII formula 

was applied to the measured one-third-octave band 

data to calculate the SII. 

Test environment and apparatus 

All testing was conducted in the Auditory Research 

Laboratory at the Pittsburgh location of the NIOSH 

Office of Mine Safety and Health Research 

(OMSHR). Testing occurred in a double-walled, 

sound-treated hearing test booth. The stimulus sounds 

were stored in digital format and were routed into the 

booth through an MPX 300 amplifier and a GrasonStadler clinical audiometer. The audiometer was used 

to adjust stimulus loudness (volume) to 1 dB 

accuracy. The sound-treated booth was outfitted with 

two diagonally-situated Cambridge Soundworks 

Model 6 speakers. A G.R.A.S. 45 CA acoustic test 

fixture (ATF) with binaural G.R.A.S. Type 40AO 1⁄2

inch pressure-field microphones was used for 

measuring the output of the SRHPDS. IEC 711 

couplers were used with the fixture to simulate the 

ear canal; this is necessary for accurate calculation of 

the SII. The ATF was positioned in the center of the 

booth atop a heavy-duty surveying tripod. Figure 1 

depicts the orientation of the speakers and ATF 

inside the test booth. 

­
 

 

FIGURE 1: ORIENTATION OF ATF AND 

SPEAKERS INSIDE THE SOUND-TREATED TEST 

BOOTH 

Data acquired from the G.R.A.S. ATF was fed to a 

National Instruments PXI 4462 4-channel data 

acquisition system and analyzed using Nelson 

Acoustics Trident software. The Trident software 

provides a real-time display of the sound levels and 

one-third-octave-band sound pressure levels for each 

microphone. The sound levels in the booth were 

confirmed using a Bruel and Kjaer 4188-A 

microphone hanging in the center of the room routed 

through the same data acquisition system and 

analyzed with the same software. 

 

Stimuli 

Mining noise sources served as the background noise 

for SII and human-subject testing. The noises of 

machinery common in underground coal mining were 

taken from recordings collected during other field 

studies by NIOSH researchers in the Office of Mine 

Safety and Health Research. The noises were from 

various operations performed with continuous mining 

machines (cutting/conveying and tramming) as well 

as the drilling operation of roof bolting machines 

(RBMs). According to data collected from 2000 to 

2002 by the Mine Safety and Health Administration 

(MSHA), 65% of miners who had noise 

overexposures operated at least one of seven types of 

mining equipment. Continuous mining machine 

operators accounted for 35% of those overexposures, 

and roof bolting machine operators accounted for 

17% [10]. Continuous mining machines (CMMs) are 

among the principal pieces of equipment used in 

underground coal mining and generate some of the 

highest sound levels. Sound levels around these 

machines can range from 78 to 109 dB(A) depending 

on the machine emissions, acoustic environment, task 

being performed, and distance from the machine [11]. 

Roof bolting machines (RBMs) are also used widely 

in underground coal mining and can produce sound 

levels ranging from 97–108 dB(A) while drilling 

[12]. The original recordings consisted of sound from 

the CMM or RBM as well as workers talking and 

other extraneous sounds. The sound files were edited 

using Adobe Audition 2.0. The resulting sounds were 

4.5 minutes long and contained only the sound 

emitted by the machine. 

The playback levels of the mining noises were 

manually adjusted using the GSI audiometer to 

achieve the desired sound level inside the booth. This 

was done using the hanging reference microphone 

and Trident software to monitor the level. CMM 

cutting/conveying at 80 and 95 dB SPL, CMM 

tramming at 78 dB SPL, and RBM drilling at 80 dB 

SPL were used as background noise during this stage 

of research. The 78 and 80 dB SPL noises used in 

this study are somewhat lower than typically 

experienced by the operators of these machines. 

However, the noise levels are realistic for the levels 

experienced by other workers in the general area of 1 the machine. 

1 During machine operation it would be very difficult 

for the operators to understand speech, regardless of hearing 

protector use, because of their proximity to the high noise levels 

emitted by the machine. By representing sound levels experienced 

by other workers in proximity of the machines, not necessarily the 

operator, we are able to determine the effects of the SRHPDS for a 

larger portion of mining occupations and with better speech 

intelligibility expectations. 

Procedure 

The first stage of the procedure involved determining 

one quarter, one half, and three quarters of potential 

acoustic output, as well as passive and maximum 

output conditions for each SRHPD. First, the full 

range of response of each SRHPD from passive to 

maximum was measured in a background of 80 dB 

SPL pink noise inside the sound-treated booth. To 

determine the full range of performance, the linear 

SPL for passive and maximum was measured using 

the Trident software with each SRHPD placed on the 

ATF. The SPL measured from the right and left sides 

of the device were averaged to obtain one overall 

number. If the two sides were not within 3 dB of each 

other, the device was adjusted for better fit on the 

fixture and re-measured. 

The minimum averaged output was subtracted from 

the maximum averaged output to determine the range 

of device amplification. Once the full range of 

amplification was determined for a device, the 
 

amplification corresponding to one quarter, fourth, 

half, and three quarters of the maximum 

amplification were calculated. For example, if the 

minimum output for a device was 58 dB and the 

maximum output was 78 dB, the range of 

amplification is 20 dB, and the dial positions for 

outputs of 63, 68, and 73 dB would relate to one 

quarter, one half and three quarters of the maximum 

amplification. This determination was made for 3 

samples of the nine SRHPDs. For simplicity, the dial 

positions corresponding to one quarter, one half, and 

three quarters of the maximum amplification will be 

referred to as the "quarter points". 

Next, an iterative process was followed to determine 

the dial positions that correspond to each of the 

calculated quarter points. Once again, pink noise was 

used to generate sound with an overall SPL of 80 dB 

inside the test booth. A device was placed on the 

ATF and the output control was adjusted to a dial 

position that was expected to produce roughly one 

quarter of the maximum output. The 30-second 

equivalent continuous sound pressure level (LEQ) 

was measured and compared to the level 

corresponding to one quarter of the maximum output. 

Based on the comparison of these values, the dial 

position was adjusted up or down and the LEQ was 

once again measured and compared to the target 

level. For each device, this process was repeated until 

the dial positions corresponding to the quarter points 

were found. The outputs obtained from the two sides 

of each device were averaged to achieve one overall 

output. 

This procedure was carried out for three samples of 

each of the 9 SRHPD models. The setting in relation 

to quarter points was marked on the device. The 

settings were acoustically and mathematically 

determined and did not necessarily reflect the visual 

or physical settings of any output controls on the 

devices in reference to percent of dial turn from the 

off or passive condition. There also were differences 

in range and quarter points across devices and within 

samples of devices of the same make. 

Next, one-third-octave-band SPLs were determined 

for the quarter points, passive, and maximum settings 

of each device in four mining background noises: 

CMM cutting/conveying at 80 dB and 95 dB SPL, 

CMM tramming at 78 dB SPL, and RBM drilling at 

80 dB SPL. Each HPD was placed on the ATF, and 

one of the noises was played in the test chamber, 

again using the audiometer to adjust the SPL in the 

test booth. A 15-second LEQ was measured at each 

device setting, and the resultant one-third-octave

band SPLs were acquired through the National 

Instruments system and exported to Microsoft Excel 

spreadsheets. For each device setting and test noise, 

three tests were performed and the average of the 

three tests was calculated. This process was followed 

for three samples of all nine SRHPDs. 

For the last stage of testing, the SII formula was 

applied to the one-third-octave band data acquired in 

the various mining noise backgrounds. Application of 

the SII formula provides an estimate of speech 

intelligibility based on the frequency spectra of the 

background noise, the speech spectrum level, and the 

band audibility function. There are four possible 

computational procedures, which take into account 

variations in band importance function, speech 

spectrum level, and noise spectrum level. Based on 

the characteristics of individual applications, the most 

applicable computation method can be chosen from 

these four options. For this research, the one-third

octave-band SII procedure was implemented. 

Equation 1 is for the calculation of SII, where n is the 

number of SII computational bands, while li and Ai 

are the values of the band importance function and 

the band audibility function. 

­

­

? SII = ∑ 1i Ai (1) i=1 

Table 3 within the standards document [7] provides 

details for specific formula application, such as 

details regarding the SII computational bands as well 

as band importance and band audibility function as 

used for the one-third-octave band computational 

procedure. 

A MATLAB program to calculate the SII was 

obtained from the SII website 

(http://www.sii.to/html/programs.html). The program 

was modified to meet our needs. First, the SPLs 

measured at the center of room microphone and the 

fixture microphones were read into the program. 

Next, the average SPL was calculated for the left and 

right microphones. The gain specific to a device, 

device setting, and noise was calculated for each one

third-octave band by equation 2: 

­
 

 

Gi = SPL/ix,i - SPL?oise,i (2) 

where G is the gain for the i

th i one-third-octave band, 

SPLfix,i is the average SPL at the fixture for the i

th 

one-third-octave band, and SPLnoise,i is the SPL at the 

microphone in the center of the test booth for the i

th 

one-third-octave band due to the played noise 

recording. This gain accounts for the passive 

attenuation of the HPD combined with the 

amplification due to the electronics. The noise 

spectrum level was then computed using equation 3: 

Ni = SPL?oise,i - BWadj,i (3) 

where BWadj,i is the bandwidth adjustment for the i

th 

one-third-octave band from Table 3 in the standard 

and Ni is the noise spectrum level for the i

th one

third-octave band. 

Next, the program calculates the equivalent speech 

and noise spectrum levels based on the measured 

noise using the standard speech spectrum levels for 

normal, raised, loud, and shout as listed in Table 3 of 

the standard. For these calculations, a distance of 1 m 

was used for the noise source to listener distance and 

binaural listening was assumed. In addition, normal 

hearing was assumed for all calculations (i.e. hearing 

level of 0 dB). 

­

RESULTS 

All responses for each device tested were averaged 

for the same setting and noise source to arrive at 

composite SII scores for each device by noise and 

setting. Devices were assigned an alphabetic code to 

assure that during analysis the devices remained 

unidentified. The results of the SII analysis showed 

that differences in the background noise source led to 

the greatest variation in estimated available speech 

cues, but little variation occurred by device or setting 

within that noise source. 

All results referenced are derived using the standard 

speech spectrum levels for “shout”. Calculated SII 

values ranged from 0.14-0.89. For the CMM 

cutting/conveying at 95 dB SPL no device or setting 

achieved an SII greater than 0.14. Based on 

recommendations within the standard for applying 

the SII [7], one cannot reasonably expect auditory 

communication with such a low SII, therefore CMM 

cutting/conveying at 95 dB SPL was not used for 

subject testing. Based on the improved SII values 

from the remaining noise sources (0.54-0.95), it was 

decided to use both remaining CMM noises and the 

RBM noise for subject testing. 

Differences in SII between the remaining three noise 

sources ranged from 0.05-0.25. However, within each 

of the three noise sources the range of SII value 

differed between each setting and device was less 

than 0.15 in most cases. Figures 2, 3, and 4 depict the 

SII value versus device for both the CMM noise 

sources. The various SRHPDs are alphabetically 

depicted in the legend. It can be seen that within a 

particular noise source, most differences between 

devices at equal settings are less than 0.15 for all 

three noise sources. Note the scale in Figure 4 is 

much less (0.1-0.2) than the scale for figures 2 and 3 

(0.5-1.0). Also note that as the setting of the SRHPD 

is increased from passive to maximum, the general 

trend is for degraded performance (figures 2 and 3), 

except for CMM cutting/conveying at 95 dB SPL 

where there is poor performance for all conditions 

(figure 4). 

 

 

 

     

1.00

D 0.95

F 0.90

I 0.85

0.80 S

Calculated SII

0.75 P

0.70 K

0.65 R

0.60 O

0.55 T

0.50

passive	 one half three maximum

quarter quarters

SRHPD Output Setting

FIGURE 2: CALCULATED SII VALUES BY DEVICE 

AND SETTING WITH RECORDING OF CMM 

TRAMMING AT 78 dB SPL AS A NOISE SOURCE. 
S BY DEVICE

OF

B

ORDING OF

T

d from best to

ice

e same order

.

e

assive,

ur ranks were

tput 

gibility

ing

VALU

WITH RECORDI

80

SII

WITH RE

order

SII within each de

showed

except for four case

performan

(4

The other f

o

estimated speech inte

tent rank order, as

settings, led to

e quarter

variables.

mples of the SPLs

he center of the test

test fixture with the

rs for the recordings

dB SPL, CM

SPL, and CM

ted

e P) to low (device

w the gain for the

ted by e

levels at the

ices tested,

und levels of 92.1,

ings with levels of

S and P, however,

els under the HPDs

each cas

ech intelligibility in

nor would it

earing because it

vels to levels that

vels.

AND OUTPUT AS

78 dB SPL

um

SRHPD Output Set

The results of the cons

well as minimal change betwee

, o

stud

show exa

measured at the microphone in

booth and under the HPDs at th

device outputs set to three quar

of CM tramming at 78

cutting/conveying at 80 d

to show a range of calcu

high (device S) to average (dev

In addition, the figures sh

same test conditions as calcu

ote that device R amplified th

much more than the other de

weighted s

98.8, and 89.9 dB for the recor

. Device

weighted sound le

at the fixture to less than 85 dB

likely improve sp

these background noise sources

good choice for protecting

amplified relatively low sound

allowable

RE 5: CALCULATED GAI

CMM TRAMMING A

 

 

 

   

 

 

 

Calculated SII

1.00

0.95

0.90

0.85

0.80

0.75

0.70

0.65

0.60

0.55

0.50

passive	 one quarter half three maxim

quarters

SRHPD Output Setting

FIGURE 3: CALCULATED SII VALUE S BY DEVICE 

AND SETTING WITH RECORDING OF CMM 

CUTTING AND CONVEYING AT 80 dB SPL AS A 

NOISE SOURCE. 

 

 

 

 

 

 

 

 

FIGURE 4: CALCULATED SII VALUES BY 

DEVICE, AND SETTING WITH REC ORDING OF 

CMM CUTTING AND CONVEYING AT 95 dB SPL 

AS A NOISE SOURCE. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When SRHPD setting was rank-ordere d from best to 

worst calculated SII within each dev ice and noise 

source, all SRHPD settings showed th e same order 

for all measures except for four cases . The order of 

settings from best to worst performanc e (highest SII 

to lowest SII) was the following: (1) passive, (2) one 

quarter output, (3) one half output, (4) three quarters 

output, and (5) maximum. The other fo ur ranks were 

only switched in that the one quarter ou tput condition 

led to better estimated speech intelli gibility than 

passive. The results of the consistent rank order, as 

well as minimal change between settings, led to the 

decision to implement passive, one quarter, and three 

quarter output as the subject study variables. 

Figures 5, 6, and 7 show exa mples of the SPLs 

measured at the microphone in t he center of the test 

booth and under the HPDs at the test fixture with the 

device outputs set to three quarte rs for the recordings 

of CM tramming at 78 dB SPL, CM 

cutting/conveying at 80 dB SPL, and CM 

cutting/conveying at 95 dB SPL. These devices were 

chosen to show a range of calcula ted SII values, from 

high (device S) to average (devic e P) to low (device 

R). In addition, the figures sho w the gain for the 

same test conditions as calcula ted by equation 2. 

Note that device R amplified the levels at the fixture 

much more than the other devices tested, which 

resulted in overall A-weighted sound levels of 92.1, 

98.8, and 89.9 dB for the recordings with levels of 

78, 80, and 95 dB SPL. Devices S and P, however, 

limited the A-weighted sound lev els under the HPDs 

at the fixture to less than 85 dB in each case. Device 

R would not likely improve spe ech intelligibility in 

these background noise sources, nor would it be a 

good choice for protecting hearing because it 

amplified relatively low sound levels to levels that 

exceed recommended allowable le vels. 

 

 

 

 

 

FIGURE 5: CALCULATED GAIN AND OUTPUT AS 

MEASURED ON ATF FOR DEVICES S, P, AND R IN 

THE CMM TRAMMING AT 78 dB SPL 

BACKGROUND NOISE. 
OUTPUT AS

, P, AND R IN

80 dB SPL

OUTPUT AS

, P, AND R IN

95 dB SPL

ices at equal

orde

ned through a

mates

sting portion.

nce

FIGURE 6: CALCULATED GAIN AN

ES

THE CMM CUTTING/CONVEYING

: CALCULATED GAIN AN

ES

THE CMM CUTTING/CONVEYING

between de

settings and noises were small, on th

or less in many cases. It was determ

es

the subject 

The chosen devices based on perform

ng was done using

quarters output

arried out using t

tramming

t 80 dB SPL

30

bject to

f

rnative words

e provided in

e

scores by set

quarters

the

cquired scores were

ettings from highest

ili

in subject speech

performed better in

g background noise

ing

ate that

umber of

eech intelligibility

owever, it must be

d that the results

red equal to actual 

plication of the SII

es likely to lead to

scores with huma

d there

settings of many of

y. The greater issue

ng the dials of such

. Both the SII and

utput of SRHPDs i

r at best equal

erformance

reduction in study

able

subject tes

the best four performing device

three

modified rhyme test (MRT) was

ses (CM

wit

requires a s

e

from a closed set of rhyming a

that work will 

comparison of

from the SI

speech intelligibility

three

were the same for 71% o

This does not indicate that the

to lowest SII or speech intellig

The largest difference

intelligibility scores was also

The subjects

dr

conve

f this research ind

to use the SII to reduce the

variables when attempting s

.

arefully applied and understo

obtained are not to be consid

A

allowed for elimination of dev

the worst speech intelligibility

show

in performance acros

the SRHPDs evaluated in the stu

turn

devices to maximum will no

benefit for speech intelligibilit

subject testing found that as the

increased there is decreasing,

speech intelligibility

the SII successfully allowed fo

variables to implement a reaso

 

 

 

 

 

 

 

FIGURE 6: CALCULATED GAIN AND OUTPUT AS 

MEASURED ON ATF FOR DEVICES S , P, AND R IN 

THE CMM CUTTING/CONVEYING AT 80 dB SPL A

BACKGROUND NOISE. 

 

 

 

 

 

 

 

 

 

 

FIGURE 7: CALCULATED GAIN AND OUTPUT AS 

MEASURED ON ATF FOR DEVICES S , P, AND R IN 

THE CMM CUTTING/CONVEYING AT 95 dB SPL A

BACKGROUND NOISE. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Additionally, differences between devices at equal 

settings and noises were small, on the order of 0.15 

or less in many cases. It was determi ned through a 

comparison of average scores that, overall, four 

devices led to slightly better SII esti mates. Those 

devices were chosen for the subject te sting portion. 

The chosen devices based on performa nce were I, S, 

K, and O. 

Subsequently, human-subject testing was done using 

the best four performing devices (I, S, K, and O) set 

to passive, one quarter and three quarters output. The 

modified rhyme test (MRT) was carried out using the 

same three mining noises (CMM tramming at 78 dB 

SPL, CMM cutting/conveying at 80 dB SPL, and 

RBM drilling at 80 dB SPL) with 30 normal hearing 

subjects. The MRT requires a su bject to determine a 

spoken word in the presence of background noise 

from a closed set of rhyming alte rnative words. Full 

details regarding that work will b e provided in a later 

publication. A comparison of th e rank order from 

best to worst scores from the SII and human-subject 

acquired speech intelligibility scores by setting 

(passive, one quarter, and three quarters) and noise 

source were the same for 71% of the individual tests. 

This does not indicate that the a cquired scores were 

equal, only that the ranking of settings from highest 

to lowest SII or speech intelligib ility score were the 

same. The largest difference in subject speech 

intelligibility scores was also between the various 

background noises. The subjects performed better in 

CMM tramming and RBM drillin g background noise 

than the CMM cutting/conveying regardless of 

SRHPD used or setting. 

ti

CONCLUSION 

The results of this research indicate that it is feasible 

to use the SII to reduce the number of potential 

variables when attempting sp eech intelligibility 

testing with human subjects. However, it must be 

carefully applied and understood that the results 

obtained are not to be conside red equal to actual 

speech intelligibility testing. Ap plication of the SII 

allowed for elimination of devic es likely to lead to 

the worst speech intelligibility scores with human 

subjects. The SII also showed there was little 

difference in performance across settings of many of 

the SRHPDs evaluated in the stud y. The greater issue 

is that contrary to intuition; turni ng the dials of such 

devices to maximum will not provide the most 

benefit for speech intelligibility . Both the SII and 

subject testing found that as the o utput of SRHPDs is 

increased there is decreasing, or at best equal SII 

values or speech intelligibility p erformance. Use of 

the SII successfully allowed for reduction in study 

variables to implement a reason able subject-testing 

protocol. 
ACKNOWLEDGEMENTS 

We would like to thank Roberta Hudak and Jessie 

Mechling for their valuable assistance in acquiring 

the ATF test results in an efficient and timely 

manner. 

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