Speech Recognition Testing: The Basics Recognition Testing: The Basics Rachel McArdle, Ph.D. Chief,...

Speech Recognition Testing: The Basics

Rachel McArdle, Ph.D. Chief, Audiology and Speech Pathology ServiceResearch Career Development Awardee, VA RR&DDepartment of Veterans AffairsBay Pines VA Healthcare System, Bay Pines, FL

Associate Professor, Communication Sciences & DisordersUniversity of South Florida, Tampa, FL

Bay Pines VA Healthcare System

Acknowledgements

This material is based upon work supported by the Department of Veterans Affairs,

Veterans Health Administration, and Office of Research and Development,

Rehabilitation Research and Development Service.

Disclaimer

The contents of this presentation do not represent the views of the Department of

Veterans Affairs or the United States Government.

Two Components of Hearing Loss

Carhart (1951)Loss of acuityLoss of clarity

Stephens (1976)Simple attenuationMajor distortions

Plomp (1978)AudibilityDistortion

Normal ImpairedAudibility

Distortion

BackgroundNoise

Speech Speech

Speech SpeechSpeech

Speech SpeechSpeech

SPEECH PERCEPTION EFFECTS OFSENSORINEURAL IMPAIRMENT

SPEECH PERCEPTION EFFECTS OFSENSORINEURAL IMPAIRMENT

Boothroyd

Audibility measures of speech

Speech recognition threshold (SRT)PurposeASHA methodRecorded materials


Speech recognition threshold (SRT)Speech recognition in quiet

Phonetically-balanced lists

-4

-2

0

2

4

6

WORD LISTS

50%

PO

INT

(dB

S/N

)

PB-50 W-22 NU No. 6 RANDOMLY SELECTED

The mean 50% points for the individual words calculated with the Spearman-Krber equation are shown for lists 1-4 of the PB-50 (triangles), of the CID W-22 (squares), and of the NU No. 6 (inverted triangles). The 12 randomly compiled lists (circles) are shown in the right half of the figure. The vertical bars indicate one standard deviation.

Wilson, McArdle, & Roberts, JAAA, 2008



Phonetically-balanced listsMLV vs recorded materials

Roeser & Clark, AT, 2008



Phonetically-balanced listsMLV vs recorded materialsSpeaker differences



Phonetically-balanced listsMLV vs recorded materialsSpeaker differencesList differences (NU 6, W-22, PB-50)

PB-50 harder than the W-22 (Hirsh et al, 1952)NU 6 harder than W-22

0

20

40

60

80

100

0

20

40

60

80

100

CO

RR

ECT

REC

OG

NIT

ION

(%)

-7 -2 3 8 -7 -2 3 8SIGNAL-TO-NOISE RATIO (dB)

PB-50

LIST 8LIST 9LIST 10LIST 11

W-22


NU No. 6


W-22NU No. 6

PB-50

MeansSpeaker Diffe

rences!

The mean percent correct recognition at four signal-to-noise ratios for the four lists of each of the three monosyllabic words list materials. The mean data for each of the lists are illustrated in the 4th quadrant. The lines with each set of data are the linear regressions used to describe the data. The 50% point for each function and the slope of the function at the 50% point are listed in Table 2. The horizontal line in each panel indicates the 50% point on each function.

Wilson, McArdle, & Roberts, JAAA, 2008

Speech-in-noise testing

Came about in the late 1960s as a way to quantify the amount of distortion Carhart & Tillman (1970) advocated for speech-in-noise testing to be part of test batteryStrom (2006) surveyed and found that less than half of dispensing professionals use some type of speech-in-noise task

SNR loss

(Killion, Seminars in Hearing, 2002)

Predicting Speech Recognition Performance in Noise

Audibility Linear Easily predicted from pure tones (i.e., AI)

COCHLEAR

#1 #2

#3

0

20

40

60

80

100

PER

CEN

T C

OR

REC

T R

ECO

GN

ITIO

N

#4

#5ROLL OVER

RETROCOCHLEAR

NORMAL

CONDUCTIVE

40

60

80

100

#1

PRESENTATION LEVEL (dB HL)

% C

orre

ct R

ecog

nitio

n Pe

rfor

man

ce



DistortionNon-linearPoor prediction from pure tones

01020304050

6070

0 4 8 12 16 20 2450% Point WORDS-IN-NOISE (dB S/B)

PUR

E-TO

NE

AVE

RA

GE

(dB

HL)

500, 1000, 2000 Hz

1000, 2000, 4000 Hz

01020304050

6070

N = 315

r = 0.44

r = 0.65



DistortionNon-linearPoor prediction from pure tonesPoor prediction from word recognition performance in quiet

0

20

40

60

80

100

0 4 8 12 16 20 24% C

OR

REC

T R

ECO

GN

ITIO

N a

t 80-

dB H

L

50% CORRECT POINT (dB S/B)

176 (45.5%)

107 (27.6%)

104 (26.9%)

Wilson & McArdle, Journal of Rehabilitation Research and Development, 2005



DistortionNon-linearPoor prediction from pure tonesPoor prediction from word recognition performance in quiet

Speech recognition in noise performance must be

measured directly!

0

2

4

6

8

10

12

14

16

18

20

21 23 1 2 4 6 8 10 12 14 16 18QUICKSIN LIST

50%

CO

RR

ECT

POIN

T (d

B S

/N)

Listeners with Normal Hearing

McArdle & Wilson, Journal of the American Academy of Audiology, 2006

0

2

4

6

8

10

12

14

16

18

20

21 23 1 2 4 6 8 10 12 14 16 18QUICKSIN LIST

50%

CO

RR

ECT

POIN

T (d

B S

/N)


Listeners with Hearing Loss

HI

NH

PUR

E-TO

NE

AVE

RA

GE

(dB

HL)

(500

, 100

0, 2

000,

& 4

000

Hz)

20 30 40 50 60 70 80AGE IN YEARS

50%

CO

RR

ECT

POIN

T (d

B S

/B)

0

10

20

30

40

50

60

-4

0

4

8

12

16

20

24

Function of Aging?

Wilson & Weakley, Journal of the American Academy of Audiology, 2005

Why measure speech-in-noise in an audiologic evaluation?

Addresses common complaint of the patientDifficulty understand speech in background noise

The data provide insight into the most appropriate amplification strategy

Directional microphones, FM systemsCounseling, realistic expectations

Speech-in-Noise Tests

Sentence testsSPINHINT QuickSINBKB-SIN

Monosyllable testsWINSPRINT

Speech Perception in Noise Test (SPIN)

The amount of semantic context leading to the last word of each sentence, which is a monosyllabic target word, is varied

50 sentences (25 LP, 25 HP)scored as the percentage of LP and HP words correctly perceived

Examples:Low Predictability (LP)Ruths grandmother discussed the broom

High Predictability (HP)The girl swept the floor with a broom

Quiet Noise +6 dB S/N

Kalikow et al, Journal of the Acoustical Society of America, 1977

TimePre Post 6-mo 1-yr

Prob

abili

ty C

orre

ct

40

60

80

100

HA-alone HP HA-alone LP HA+AR HP HA+AR LP

HighPredictability

N = 105

LowPredictability

Hearing in Noise Test (HINT) 10 BKB sentences- 1st grade reading level

Repeat entire sentence correctly bracketing methodDecrease signal for correct answerIncrease signal for incorrect answer

Speech spectrum noise - fixedScored in terms of signal-to-noise ratio at the 50% point

Example:

Her shoes were very dirty

Quiet Noise (3 dB S/N)

Nilsson et al, Journal of the Acoustical Society of America, 1994

HINTNoise = 70 dB HL

# List 1 - practice Level List 1 Level

1 2

2 3

3 4

4 5

5 6

6 7

7 8

8 9

9 10

(A/The) boy fell from (a/the) window




(A/The) wife helped her husband






Big dogs can be dangerousHer shoes (are/were) very dirty(A/The) player lost (a/the) shoeSomebody stole the money(A/The) fire (is/was) very hotShe's drinking from her own cup(A/The) picture came from (a/the) book(A/The) car (is/was) going too fast

84+82+84+82+80+82+84/7 = 82.6 (signal) 70 dB HL (noise)

50% point = 12.6 dB S/N

BKB Speech-in-Noise Test (BKB-SIN) 10 BKB sentences- 1st grade reading level

3 target words per sentence Multitalker babbleDescending paradigm +21 to -6 dB S/N

3 dB decrementsScored in terms of signal-to-noise ratio at the 50% pointGood for CI users, children, and profound hearing loss

Example:

The bag fell to the ground


Etymotic Research, 2005

BKB-SIN Test List 4A1. A mouse ran down the hole. 4 +212. The light went out 3 +183. They wanted some potatoes 3 +154. The little girl is shouting 3 +125. The cold milk is in a pitcher 3 + 96. The paint dripped on the ground 3 + 67. Mother stirred her tea 3 + 38. The father is coming home 3 0 dB9. She had her spending money. 3 - 310. He is bringing his raincoat 3 -6

xx x

xx xxx x x

xx x

4333321000

19SNR 50%= 23.5 19 = 4.5 dB

Spearman-Krber Equation(Finney, 1952)

50% = i + (d) (d)(# correct)/(w)i = the initial presentation level (dB S/B)d = the attenuation step size (decrement)w = the number of items per decrement.

BKB Example:Initial starting level 21 dB S/N, 3 dB step size, 3 words per decrement # correct = 15

50% = 21 + (3) (3)(15)/350% = 21 + 1.5 - 1550% = 22.5 +1* 15 50% = 23.5 15 = 8.5 dB S/N

Quick Speech-in-Noise Test (QuickSIN)

6 IEEE sentences-5 target words per sentenceSyntactic cues but subtle semantic cues

Multitalker babble Descending paradigm 25-to 0-dB S/N

5 dB decrementsScored in terms of signal-to-noise ratio at the 50% point (Spearman-Krber equation)

Quiet Noise (5 dB S/N)Example:

It is a band of steel 3 inches wide

Killion et al, Journal of the Acoustical Society of America, 2004

QuickSIN List 1A white silk jacket goes with any shoe. S/N 25 The child crawled into the dense grass. S/N 20 Footprints showed the path he took up the beach. S/N 15 A vent near the edge brought in fresh air. S/N 10 It is a band of steel three inches wide. S/N 5 The weight of the package was seen on the high scale. S/N 0

xxx x

25.5 Total Correct = SNR Loss

xxxx

xx

SCORE554330

QuickSIN Example:Initial starting level 25 dB S/N, 5 dB step size, 5 words per decrement # correct = 20

50% = 25 + (5) (5)(20)/550% = 25 + 2.5 - 2050% = 27.5 20 = 7.5 dB S/NSNR loss 50% = 25.5 20 = 5.5 dB S/N

0

10

20

30

40

50

60

70

80

90

100C

OR

REC

T W

OR

D R

ECO

GN

ITIO

N (%

)

25

21 23 1 2 4 6 8 10 12 14 16 18QUICKSIN LIST

5

10

1520

Stimulus variability

Dimes showered down from all sides

It was done before the boy could see it

n = 72 listeners with hearing loss


-4

-3

-2

-1

0

1

2

3

4

1 2 4 6 8 10 12 14 16 18QUICKSIN LIST

DEV

IATI

ON

FR

OM

MEA

N 5

0% P

OIN

T (d

B)


-4

-3

-2

-1

0

1

2

3

4

1 2 6 8 10 12 16 17QUICKSIN LIST

DEV

IATI

ON

FR

OM

MEA

N 5

0% P

OIN

T (d

B)

11


Words-in-Noise Test (WIN)35 NU No. 6 monosyllabic words (female speaker)

5 words per signal-to-noise ratio Multitalker babble - fixedDescending paradigm 24-to 0-dB S/N

4-dB decrementsScored in terms of signal-to-noise ratio at the 50% point (Spearman-Krber equation)

Example:

Say the word voice


Wilson, Journal of the American Academy of Audiology, 2003

List 1, Random 2 24-dB S/B 12-dB S/B 0-dB S/B

1 FOOD 16 RUSH 31 BATH 2 PAIN 17 VOICE 32 DAB 3 LATE 18 TOOL 33 GET 4 DODGE 19 SEARCH 34 READ 5 COOL 20 GOOD 35 LIFE

20-dB S/B 8-dB S/B 6 DITCH 21 MAKE # Correct 7 KICK 22 SOAP 8 LUCK 23 YOUNG 9 GUN 24 SOUR

10 SUCH 25 HALF 16-dB S/B 4-dB S/B

11 WIRE 26 SHEEP 12 TIME 27 MESS 13 HAVE 28 MOOD 14 JUDGE 29 LONG 15 DOG 30 FAR

x

x

x

xxxxx

17

WIN Example:Initial starting level 24 dB S/N, 4 dB step size, 5 words per decrement # correct = 17

50% = 24 + (4) (4)(17)/550% = 24 + 2 17(0.8)*50% = 26 13.6 = 12.4 dB S/N

*The "0.8" is the attenuation step size (4 dB) divided by the number of words per step (5)

Name_______________________SS#__________Age__________ Date____________By__________Ear___________Level________

24-dB S/B 12-dB S/B 0-dB S/B1 pain 16 hate 31 gaze 2 youth 17 shack 32 life 3 wheat 18 tool 33 get 4 dodge 19 voice 34 read 5 cool 20 rush 35 bath

20-dB S/B 8-dB S/B 6 ditch 21 turn # Correct7 ring 22 young 8 kick 23 bite 9 chair 24 pick

10 luck 25 half 16-dB S/B 4-dB S/B

11 base 26 far 12 wire 27 learn 13 red 28 mood 14 time 29 talk 15 judge 30 note

Threshold (50%) dB S/B

Track 25, List 1, Random 1

Ear_________Level______________

24-dB S/B 12-dB S/B 0-dB S/B1 food 16 good 31 back 2 road 17 search 32 dab 3 juice 18 pass 33 kill 4 late 19 witch 34 nice 5 hire 20 chief 35 calm

20-dB S/B 8-dB S/B 6 tire 21 sour # Correct7 such 22 doll 8 shawl 23 deep 9 haze 24 soap

10 gun 25 make 16-dB S/B 4-dB S/B

11 live 26 beg 12 date 27 mess 13 gas 28 long 14 have 29 mouse 15 dog 30 sheep

Threshold (50%) dB S/B

Track 26, List 2, Random 1

# C

orre

ct

Thre

shol

d

1 25.2 2 24.4

3 23.6PROFOUND 4 22.8

5 22.06 21.27 20.48 19.69 18.810 18.0SEVERE11 17.212 16.413 15.614 14.815 14.016 13.2MODERATE17 12.418 11.619 10.820 10.021 9.2

MILD 22 8.423 7.624 6.825 6.026 5.227 4.428 3.629 2.8

NORMAL 30 2.0 31 1.2 32 0.4 33 -0.4 34 -1.2 35 -2.0

Speech Recognition in Noise Test (SPRINT)

200 NU No. 6 monosyllabic words (male speaker)6-talker babble Fixed paradigm (9 dB S/N)Scored in terms of # correct out of 200

Example: Quiet Noise (9 dB S/N)

Say the word room

Cord MT, Walden BE, Atack RM, 1992

20

40

60

80

100

0 4 8 12 16 20 2450% POINT (dB S/N)--WIN

PER

CEN

T C

OR

REC

T--S

PRIN

T

0

R=-0.81

Wilson & Cates, Journal of the American Academy of Audiology, 2008

0

20

40

60

80

100

0 4 8 12 16 20 24SIGNAL-TO-NOISE RATIO (dB)

PERC

ENT

CO

RRE

CT

REC

OG

NIT

ION

PRESENTATION LEVEL (dB HL)--WIN60 64 68 72 76 80 84

S

S

Wilson & Cates, Journal of the American Academy of Audiology, 2008

How do you select a test?

Factors to consider when selecting a speech-in-noise test

Easy to Administer

HINT

QuickSIN

BKB-SIN

WIN

Ease of Administration

Adaptive protocol (i.e., HINT)Audiologist manually adjusts the signal-to-noise ratioBracketing method

Use initial sentence to determinestarting levelDecrease the level after a

correct responseIncrease the level after an incorrect response

2010

0

30

4050

60 70

80

Ease of AdministrationDescending Paradigm (i.e., QuickSIN, BKB-SIN, WIN)

Materials are recorded at multiple signal-to-noise ratios that are presented in a descending mannerDecrement in dB S/N for a particular material is fixedAllows for calculation of the 50% point utilizing the Spearman-Krber equation Allows for stopping rule (i.e., WIN)


Ease Test Time

HINT

QuickSIN

BKB-SIN

WIN


Ease Test Time

HINT 1.5 min*

QuickSIN

BKB-SIN

WIN


Ease Test Time

HINT 1.5 min*

QuickSIN 1min

BKB-SIN

WIN


Ease Test Time

HINT 1.5 min*

QuickSIN 1min

BKB-SIN 1.5 min

WIN


Ease Test Time

HINT 1.5 min*

QuickSIN 1min

BKB-SIN 1.5 min

WIN 2 min


Ease Test Time

Basic Auditory Fx

1.5 min*

1min

1.5 min

2 min

Context

HINT

QSIN

BKB-SINWIN

Miller, Heise, Lichten, Journal of Experimental Psychology, 1951

Words or Sentences?

Advantages of sentencesMore realistic stimulus-type when examining how fluent speech is perceived High face validityShorten test administration time

Disadvantages of sentencesAdditional cognitive demands Syntactic and semantic structure of sentence-length stimuli influences performance making it difficult to determine basic auditory function

Advantages of monosyllablesMinimize the effects of working memory and linguistic context on performanceMost popular stimulus type among audiologists

Disadvantages of monosyllablesNot representative of everyday speech Lack natural dynamics of real speech such as word stress, co-articulation, and dynamic range

0

4

8

12

16

20

24

50%

Poi

nt W

IN (d

B S

/B)

0 4 8 12 16 20 2450% Point QuickSIN (dB S/B)

(29--40%)

(43--60%)

Wilson & McArdle, Journal of Rehabilitation Research and Development, 2005


Ease Test Time

Basic Auditory

Fx

Context

1.5 min

1 min

1.5 min

2 min

HINT

QSIN

BKB-SINWIN

Ease Test Time

Basic Auditory

Fx

Context

1.5 min

1 min

1.5 min

2 min

Best Separation

HINT

QSIN

BKB-SIN

WIN


Mean Recognition performances for the NU No.6 in multitalker babble (WIN test)

WIN data

Signal-to-noise ratio (dB)-10 0 10 20 30 40

Wor

ds c

orre

ct (%

)

0

20

40

60

80

100

Normals (n=24)Mild/Moderate Loss (n=72)

% C

OR

REC

T R

ECO

GN

ITIO

N a

t 104

-dB

SPL

50% CORRECT POINT (dB S/B)

QuickSIN

HINT

-2 2 6 10 14 18 22 -2 2 6 10 14 18 22

WIN

0

20

40

60

80

100

0

20

40

60

80

100 BKB-SIN

22% 78% 28% 72%

10% 90% 1% 99%

Wilson, McArdle, & Smith, JSLHR, 2007

Ease Test Time

Basic Auditory

Fx

Context

1.5 min

1 min

1.5 min

2 min

Best Separation

HINT

QSIN

BKB-SIN

WIN


Recognition performance varies as a function of presentation level

Presentation Level on Speech in Noise Recognition Performance

0

20

40

60

80

100

70 80 90 100 110 120 130

PRESENTATION LEVEL (dB SPL)

% C

OR

REC

T R

ECO

GN

ITIO

N

15-dB S/N

0-dB S/N

P&P

KP&P

K

Kryter, Journal of the Acoustical Society of America, 1946Pollack & Pickett, Journal of the Acoustical Society of America, 1958

Where to purchase tests

WIN email [email protected] CD

QuickSIN/BKB-SIN www.etymotic.comQuickSIN - $160BKB-SIN - $195

HINT Bio-logic Systems Corp Karen Plude800-323-8326 ext 239sales @ bio-logic.com

mailto:[email protected]://www.etymotic.com/

AcknowledgmentsRichard Wilson, PhD

James H. Quillen VA, Mountain Home, TNSherri Smith, AuD/PhD

James H. Quillen VA, Mountain Home, TN

Bay Pines Auditory Research Lab (past and present)Mitzy Carlo, AuD/PhDMonica Mejia, AuDElizabeth Townsend, AuDJana Wells, AuDCassie Eiffert, AuDLiz Talmage, AuDVicky Williams, BALynette Dornton, BS

REFERENCES

Carhart R. Basic principles of speech audiometry. Acta Otolaryngol. 1951;40:62-71.Cord, Walden, Atack (1992) Unpublished paper. Walter Reed Army Medical Hospital.BKB-SIN Speech-in-Noise Test [compact disk]. Elk Grove Village (IL): Etymotic Research, Inc.;2005.Kalikow DN, Stevens KN, Elliott LL. Development of a test of speech intelligibility in noise using sentence materials with controlled word predictability. J Acoust Soc Am. 1977;61:1337-1351.Killion MC. New thinking on hearing in noise: a generalized articulation index. Sem Hear. 2002;23:57-75.Killion MC, Niquette PA, Gudmundsen GI, Revit LJ, Banerjee S. Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners. J Acoust Soc Am. 2004;116(4 Pt 1):2395-2405.Kryter KD. Effects of ear protective devices on the intelligibility of speech in noise. J Acoust Soc Am. 1946;18(2):413-417.McArdle RA, Wilson RH, Burks CA. Speech recognition in multitalker babble using digits, words, and sentences. J Am Acad Audiol. 2005;16:726-739.McArdle, R., & Wilson, R.H. (2006). Homogeneity of the 18 QuickSIN Lists. Journal of the American Academy of Audiology, 17(3), 157-167.Miller GA, Heise GA, Lichten W. The intelligibility of speech as a function of the context of the test materials. J Exp Psychol. 1951;41(5):329-335.Nilsson M, Soli SD, Sullivan JA. Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. J Acoust Soc Am. 1994(2);95:1085-1099.Plomp R. Auditory handicap of hearing impairment and the limited benefit of hearing aids. J Acoust Soc Am. 1978;63(2):533-549.

Pollack I, Pickett JM. Masking of speech by noise at high sound levels. J Acoust Soc Am. 1958;30(2):127-130.Shanks JE, Wilson RH, Larson V, Williams D. Speech recognition performance of patients with sensorineural hearing loss under unaided and aided conditions using linear and compression hearing aids. Ear Hear. 2002;23(4):280-290.Stephens SDG. The input for a damaged cochlea: a brief review. Brit J Audiol. 1976;10:97-101. Wilson RH. J Rehab Res & Dev. 2003Strom KE. The HR 2003 dispenser survey. Hear Rev. 2003;10(6):22-38.Wilson RH. Development of a speech-in-multitalker-babble paradigm to assess word-recognition performance. J Am Acad Audiol. 2003;14(9):453-470.Wilson RH, Burks CA, Weakley DG. Word recognition of digit triplets and monosyllabic words in multitalker babble by listeners with sensorineural hearing loss. J Am Acad Audiol. 2006 17:385-398.Wilson RH, McArdle RA. Speech signals used to evaluate functional status of the auditory system. J Rehab Res & Dev. 2005;42(Suppl 2):79-94.Wilson RH, Weakley DG. The 500 Hz masking-level difference and word recognition in multitalker babble for 40- to 89-year-old listeners with symmetrical sensorineural hearing loss. J Am Acad Audiol. 2005;16(6):367-382.Wilson RH, Weakley DG. The use of digit triplets to evaluate word-recognition abilities in multitalker babble. Seminars in Hearing. 2004;25(1):93-111

Speech Recognition Testing: The BasicsAcknowledgementsDisclaimerTwo Components of Hearing LossAudibility measures of speechAudibility measures of speechAudibility measures of speechAudibility measures of speechAudibility measures of speechSpeech-in-noise testingPredicting Speech Recognition Performance in NoisePredicting Speech Recognition Performance in NoisePredicting Speech Recognition Performance in NoisePredicting Speech Recognition Performance in NoiseWhy measure speech-in-noise in an audiologic evaluation?Speech-in-Noise TestsSpeech Perception in Noise Test (SPIN)Hearing in Noise Test (HINT)HINTBKB Speech-in-Noise Test (BKB-SIN)Spearman-Krber Equation(Finney, 1952)Quick Speech-in-Noise Test (QuickSIN)QuickSIN List 1Words-in-Noise Test (WIN)Speech Recognition in Noise Test (SPRINT)How do you select a test?Factors to consider when selecting a speech-in-noise testEase of AdministrationEase of AdministrationFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testWords or Sentences?Factors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testFactors to consider when selecting a speech-in-noise testWhere to purchase testsAcknowledgments

Speech Recognition Testing: The Basics Recognition Testing: The Basics Rachel McArdle, Ph.D. Chief,...

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