Journal of Speech and Hearing Research, Volume 33, 726-735, December 1990

Hearing impairment is the third most prevalent chronicdisability identified by those over the age of 65 (NCHS,1977). In addition, the elderly consider disabilities in-volving communication to be of greatest consequence(Jacobs-Condit, 1984). With the prevalence of hearingloss at 25-40% for individuals over 65 years of age(Herbst, 1983; NCHS, 1977, 1986), deficits in speechunderstanding associated with hearing loss represent themajor component of elderly persons' communication dis-ability. The research described here seeks to gain a betterunderstanding of the hearing-related speech-recognitiondeficits experienced by this rapidly growing segment ofsociety.

Evaluation of the speech understanding problems ofthe elderly is difficult because speech recognition innormal-hearing young adults is itself a complex process.Most contemporary models of the speech-recognitionprocess, however, include a common core of underlyingmechanisms (Klatt, 1988; Pisoni, 1978; Pisoni & Luce,1987). Mechanisms common to most models of thespeech-recognition process include, for example (a) aperipheral encoding process that produces an internalrepresentation of the acoustic stimulus; (b) brief storageof the encoded input in a modality-specific sensory mem-ory; (c) transfer of some portion of the information insensory memory to primary (short-term) memory; and (d)access to secondary (long-term) memory (which containsknowledge of phonology, syntax, semantics, etc.) fromprimary memory. Disruption of any one of the mecha-nisms involved in the speech-recognition process couldpotentially result in a deficit in speech recognition.

Because the peripheral portion of the auditory system,especially the cochlea and auditory nerve, are known todeteriorate with age, examination of age differences inthe peripheral encoding process is a logical place to beginan investigation of the factors underlying the speech-recognition problems experienced by the elderly. Themost obvious and well-documented peripheral deficit in

the elderly is the presence of a high-frequency senso-rineural hearing loss (eg., Bunch, 1929, 1931; Corso,1959; Spoor, 1967). Although understanding the speech-recognition deficits of young listeners with sensorineuralhearing loss is itself a challenging task, significant inroadshave been made in this area in recent years. For manyyoung hearing-impaired listeners, variations of the Artic-ulation Index (AI) originally described by French andSteinberg (1947) and Fletcher and Galt (1950) haveproven to provide an accurate prediction of speech-recognition performance (Aniansson, 1974; Dirks, Bell,Rossman, & Kincaid, 1986; Dubno & Dirks, 1989; Dubno,Dirks, & Schaefer, 1989; Dugal, Braida, & Durlach, 1980;Humes, Dirks, Bell, Ahlstrom, & Kincaid, 1986; Kamm,Dirks, & Bell, 1985; Macrae & Brigden, 1973; Pavlovic,1984; Pavlovic, Studebaker, & Sherbecoe, 1986). Thesuccess of this index as a predictor of speech-recognitionperformance for most of the young hearing-impairedpopulation confirms the primary importance of speech-spectrum audibility in explaining the speech-recognitiondeficits of this group. That is, various hypothesized addi-tional forms of distortion, such as excessive upwardspread of masking, broader critical bandwidths, and soforth, are not incorporated into the AI, and yet it providesa good estimate of the speech-recognition performance ofthe young hearing-impaired.

The AI approach can only be considered successful,however, for nonreverberant speech. Actually, the AIitself does not provide a good prediction of the recogni-tion of reverberant speech, even in normal listeners(Humes et al., 1986). Rather, an alternative index basedon a combination of the AI and a related index, theSpeech Transmission Index (STI) (Houtgast & Steene-ken, 1985; Steeneken & Houtgast, 1980), has been devel-oped for application to the recognition of both temporallydistorted and nondistorted speech by the young hearing-impaired. This index, referred to as the modified STI, ormSTI (Humes, Boney, & Loven, 1987; Humes et al.,

© 1990, American Speech-Language-Hearing Association

SPEECH-RECOGNITION DIFFICULTIES OF THE HEARING-IMPAIRED ELDERLY: THE CONTRIBUTIONS OF AUDIBILITY

LARRY E. HUMES LISA ROBERTSIndiana University

The role that sensorineural hearing loss plays in the speech-recognition difficulties of the hearing-impaired elderly is examined.One approach to this issue was to make between-group comparisons of performance for three groups of subjects: (a) youngnormal-hearing adults; (b) elderly hearing-impaired adults; and (c) young normal-hearing adults with simulated sensorineuralhearing loss equivalent to that of the elderly subjects produced by a spectrally shaped masking noise. Another approach to thisissue employed correlational analyses to examine the relation between audibility and speech recognition within the group ofelderly hearing-impaired subjects. An additional approach was pursued in which an acoustical index incorporating adjustmentsfor threshold elevation was used to examine the role audibility played in the speech-recognition performance of thehearing-impaired elderly. A wide range of listening conditions was sampled in this experiment. The conclusion was that theprimary determiner of speech-recognition performance in the elderly hearing-impaired subjects was their threshold elevation.

KEY WORDS: speech recognition, elderly, reverberation, binaural, hearing impaired1

726 0022-4685/90/3304-0726$01.00/0

HUMES & ROBERTS: Speech Recognition by the Elderly 727

1986), has seen limited application to the recognition ofreverberant speech by young hearing-impaired listeners.Application of the mSTI to the recognition of reverberantspeech by elderly hearing-impaired listeners needs fur-ther evaluation. It may, however, offer an objective acous-tically-based prediction of how the listener should per-form for a given set of acoustic conditions and amount ofhearing loss. In that case, greater-than-expected speech-recognition difficulties in the young and elderly hearingimpaired could be expressed in quantitative terms. Thiswould greatly facilitate research on aspects of hearingloss for speech that cannot be explained by the audio-gram.

Recent studies have demonstrated that the speechunderstanding deficits of the young hearing-impaired canalso be simulated with reasonable accuracy by introduc-ing a spectrally shaped masking noise into the same earreceiving the speech (Fabry & Van Tasell, 1986; Humes,Dirks, Bell, & Kincaid, 1987; Zurek & Delhorne, 1987).The noise provides an effective simulation of both theloss of audibility and the reduced dynamic range associ-ated with sensorineural hearing loss. None of these stud-ies, which all used young hearing-impaired listeners,incorporated temporally degraded speech. It is possiblethat the spectral distortion associated with the hearingloss will interact with the temporal distortion of thespeech signal to produce a combined deficit greater thanthat expected from the simple sum of the two distortionprocesses (Lacroix & Harris, 1979; Lacroix, Harris, &Randolph, 1979). The elderly are known to have particu-lar difficulty understanding temporally degraded speech,such as reverberant speech (Bergman, 1980; Duquesnoy& Plomp, 1980; Helfer & Wilber, 1990; Nabelek &Robinson, 1982). It is not clear whether the performanceof elderly hearing-impaired listeners with reverberantspeech can be simulated by the introduction of a spec-trally shaped noise into the ear of a normal listener orwhether the performance of these subjects can be pre-dicted accurately by acoustical indices, such as the mSTI.These issues were investigated in this project.

METHOD

Subjects

A total of 36 subjects participated in this study. Twenty-three of these subjects were normal-hearing young adultsranging in age from 19-34 years and having normalhearing [pure-tone air-conduction threshold < 15 dB HL(ANSI, 1969) from 250-8000 Hz] and normal immittancemeasurements (normal tympanograms and acoustic re-flexes present in response to contralateral presentation ofa 100-dB HL 1000-Hz tone) bilaterally. Ten of the 23normal subjects served as noise-masked normal listeners;a spectrally shaped masking noise was introduced intothe left ear to simulate the sensorineural hearing loss ofthe elderly hearing-impaired subjects.

Thirteen subjects comprised the elderly hearing-im-paired group. These subjects ranged in age from 65 to 75years, with a mean age of 71.2 years. All subjects hadbilaterally symmetrical (interaural threshold differences< 20 dB at all frequencies, typically < 15 dB) slopinghigh-frequency sensorineural hearing loss with normalimmittance measurements (as defined above). The meansand standard deviations for the air-conduction thresholdsfrom each ear for the subjects in this group are shown inFigure 1. At the high frequencies, the right ear of theimpaired listeners was on the average 7 dB more sensi-tive than the left ear. All of the elderly hearing-impairedsubjects had hearing loss attributed to presbycusis and allsubjects in every group were native speakers of English.

Materials/Apparatus

The materials used in the speech-recognition testingconsisted of the full 11-subtest version of the City Uni-versity of New York (CUNY) Nonsense Syllable Test(NST) (Resnick, Dubno, Hoffnung, & Levitt, 1975). TheNST was chosen for use in this experiment for severalreasons. First, it is a reliable test using a closed-setresponse format (Dubno & Dirks, 1982; Humes et al.,1987). Second, high frequencies (1000-4000 Hz) are themost important frequency region contributing to the un-derstanding of these nonsense syllables (Humes et al.,1986; Humes et al., 1987; Kamm et al., 1985), and this isthe frequency region in which audibility was reduced inthe elderly hearing-impaired subjects of this study. Third,previous studies of the relations between the modifiedSpeech Transmission Index (mSTI), an acoustical indexto be used in this study, and speech recognition perfor-mance have used the NST as the measure of speechrecognition (Humes et al., 1986; Humes et al., 1987).

We were interested in sampling the speech recognitionperformance of the hearing-impaired elderly for a wide

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FIGURE 1. Mean pure-tone air-conduction thresholds for leftand right ears of the elderly hearing-impaired subjects (unfilledsquares and circles, respectively). Vertical bars represent onestandard deviation about the mean. Mean masked thresholds forthree normal listeners with simulated hearing loss appear as thefilled squares.

728 Journal of Speech and Hearing Research 33 726-735 December 1990

range of acoustic conditions. The NST was re-recorded inquiet and noise and in both an anechoic and a reverberantenvironment. The materials were re-recorded throughthe left and right ears of the Knowles Electronics Manikinfor Auditory Research (KEMAR) (Burkhard & Sachs,1975) with an equalization network (Killion, 1979) used toeliminate KEMAR's ear canal response during the re-recording process. In addition, two noise locations wereused: 0° and 90 ° azimuth (900 to the right of KEMAR'smidline). This represented a total of six re-recordingconditions: all combinations of three signal-and-noiseconditions (no noise, noise at 0°, noise at 90°) and tworeverberation conditions (no reverberation, reverbera-tion). A total of six experimental tapes were generated,with a different randomization of the NST used for eachcondition.

The experimental tapes were generated as follows. Aportable Marantz cassette tape deck was used to play thecommercially produced recordings (Cosmos DistributingCo.) of the NST materials. One channel of the tape deckcontained the nonsense syllables and the other channelcontained the cafeteria noise used as competition withthe NST. The outputs of each channel of the tape deckwere routed to separate channels of an amplifier (Crown,D-75) and delivered to separate matched loudspeakers(Radio Shack, Minimus-7). Both loudspeakers were posi-tioned inside a large (14' x 10' x 8') anechoic chamber,56 inches from an omnidirectional microphone posi-tioned at the center of the room. The speech loudspeakerwas always positioned at 0° azimuth and at a heightcorresponding to KEMAR's eye level. The omnidirec-tional microphone was positioned in the unobstructedsound field at a point corresponding to the center ofKEMAR's head. The noise loudspeaker transduced therecorded cafeteria noise and was positioned immediatelyadjacent to the speech loudspeaker (nominally 0° , butreally 3-40 azimuth, slightly right of KEMAR's midline)or at 90 ° azimuth. The level of the calibration tone wasadjusted to produce a level of 75 dB SPL for the speechchannel and 70 dB SPL for the noise channel whenmeasured in the unobstructed sound field with the omni-directional microphone. The calibration-tone voltages atthe loudspeaker terminals required for this acoustic out-put were noted. KEMAR was then positioned at thelocation of the omnidirectional microphone. Recordingswere made through the left and right ears of KEMARusing occluded ear simulators (ANSI, 1989) terminatedby ER-11, 2-inch microphones. The microphone outputswere then equalized (Killion, 1979) prior to recording toeliminate the ear canal response of KEMAR. The left earand right ear outputs were routed to separate channels ofan additional portable Marantz tape deck for re-recordingof the KEMAR-processed materials. The record levelswere adjusted so as to produce a peak VU-meter deflec-tion of -2 dB, for both channels, for the word "mark" ofthe carrier phrase, "You will mark... please" whentransduced by the speech loudspeaker. Three experimen-tal tapes were constructed in this fashion, one for eachnoise condition (quiet, noise at 0° azimuth, noise at 90°

azimuth). At the beginning of each tape, the 400-Hz

calibration tone was recorded through KEMAR from thespeech loudspeaker located at 00 azimuth.

Once the recordings were completed in the anechoicchamber, the tape decks, amplifier, cables, microphones,and KEMAR were removed and set up in an identicalmanner in an adjacent reverberant chamber. The averagereverberation time of this specially constructed chamberwas 3.1 s with the measured octave-band reverberationtimes provided in Table 1. The reverberation times weredefined as the time required for the rectangularly-gatedtest signal to decay 60 dB after offset. The volume of thereverberation room was equivalent to that of the anechoicchamber.

After the equipment was set up as in the anechoicchamber, the calibration tones were delivered to thespeech and noise loudspeakers, and the drive voltage atthe loudspeaker terminals was adjusted to match thatnoted for the anechoic recordings. The word "mark" fromthe carrier phrase used in the NST was again used tobalance the record levels for the two channels at -2 dBon the VU meters. Three additional experimental tapeswere generated in the reverberant chamber, each dupli-cating a condition from the anechoic chamber.

The six experimental tapes were played back through atwo-channel cassette tape deck (Sansui, D-W9). The out-put of this tape deck was routed to a two-channel ampli-fier (McIntosh, C24) and delivered to a network of 13pairs of matched TDH-39 earphones mounted in MX-41/AR cushions. Playback levels were specified as thelevel of the 400-Hz calibration tone, recorded throughKEMAR on the experimental tapes made in the anechoicchamber, generated in an NBS-9A 6-cc coupler. Outputcould be routed to the right ear, left ear, or both ears forall subjects.

The spectrally shaped masking noise used to simulatethe sensorineural hearing loss of the elderly hearing-impaired listeners was generated as follows. The outputof a random-noise generator (GenRad, 1390-B) wasshaped by a V3-octave-band equalizer (Industrial Re-search Products, TEQ DG-4023), amplified (Crown,D-75) and sent to one input of a custom-made mixer. Theoutput of a second random-noise generator (Grason Stad-ler 901B) was routed through a high-pass filter (Kemo,VBF-25MD), having a cut-off frequency of 3.7 kHz and arejection rate of 135 dB/octave, amplified (Crown, D-75)and sent to another input of the custom-made mixer. Theoutput of the mixer was then sent to the input of a digitalaudio tape recorder (Panasonic, SV-3500). On playback,the output of this tape deck was routed through the sameamplifier used for the speech testing. Before recording

TABLE 1. Octave-band reverberation times (To) in secondsmeasured in the reverberation chamber used in this study.

Octave-band 125 250 500 1000 2000 4000 8000centerfrequency(Hz)

T60 3.8 4.1 4.9 4.0 2.2 1.9 0.6

HUMES & ROBERTS: Speech Recognition by the Elderly 729

the spectrally shaped noise on the digital tape, the octaveband levels required to produce masked thresholdsequivalent to the quiet thresholds of the elderly hearing-impaired subjects were calculated using the critical ratio.Acoustically measured octave-band levels were thenadjusted to achieve these target values by manipulatingthe controls of the ¼V-octave equalizer and the amplifiers.Masked pure-tone thresholds were measured in threenormal-hearing young adults using the same clinicalprocedures with which the quiet thresholds were ob-tained from the elderly hearing-impaired listeners. Themean masked thresholds obtained in the presence of thespectrally shaped noise are shown as the filled squares inFigure 1. The masked thresholds are in general agree-ment with the mean quiet thresholds of the elderlyhearing-impaired listeners. The individual thresholds ofthe three noise-masked normal listeners never differed bymore than 5 dB at any frequency. The spectrally shapednoise was then recorded and mixed, during speech-recognition testing, with the speech signal in the left earfor those subjects with simulated hearing loss.

Procedures

By presenting the six experimental recordings to bothears, only the right ear, or only the left ear of each subject,a total of 18 test conditions was created. The full 11-subtest (102-item) NST was presented to each subject foreach of the 18 conditions, with the order of presentationrandomized across conditions. Speech materials werepresented at an overall SPL of 75 dB. Multiple-choiceanswer forms were provided, with a separate subtestrepresented on each page of the form. Subjects wereinstructed to mark the nonsense syllable heard on eachtrial and were encouraged to guess if necessary. Alltesting was completed in a large acoustically treatedsound room having noise levels less than those requiredfor threshold measurements with headphones (ANSI,1977). Approximately 6-7 hours were required for thesubjects to complete the testing in this experiment. Allsubjects were paid for their participation.

RESULTS AND DISCUSSION

Figure 2 contains the mean percent-correct scores foreach of the 18 listening conditions and all three subjectgroups. Vertical bars represent the scores from the youngnormal-hearing (unfilled bars) and elderly hearing-im-paired subjects (filled bars). The filled diamonds repre-sent the mean values for the young normal-hearing lis-teners with simulated hearing loss. Note that there arescores for only six conditions for the noise-masked normallisteners because the hearing loss was simulated for onlythe left ear. The means and standard deviations for thedata in Figure 2 are provided in numerical form in Table2.

Separate mixed-design analyses of variance (ANOVAs)were performed on the data in each panel of Figure 2

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FIGURE 2. Mean scores on the CUNY NST as a function oflistening condition (right, left, or binaural: R, L, or Bin). Toppanel shows data for quiet, middle panel for noise at 0° azimuth,and bottom panel for noise at 900 azimuth. Left half of each panelcontains data for anechoic conditions (T6 = 0.0 seconds), andright half of each panel shows data for reverberant conditions(T60 = 3.1 seconds). In each panel, unfilled bars represent scoresfrom normal-hearing young adults, filled bars represent scoresfrom elderly hearing-impaired subjects, and filled diamondsrepresent scores from normals with simulated hearing loss.

730 Journal of Speech and Hearing Research

TABLE 2. Means (M) and standard deviations (SD) of percent-correct scores for the 18 listeningconditions.

Acoustic conditionListening Quiet Noise at 00 Noise at 900

Group condition T= 0.0 3.1 0.0 3.1 0.0 3.1

Normal hearing R M 97.3 79.0 80.9 61.8 73.5 60.2SD 2.5 5.2 7.7 5.2 5.1 3.0

L M 96.1 78.8 86.8 64.2 90.8 67.8SD 1.9 5.1 3.8 4.6 2.5 4.2

Bin M 96.7 81.9 86.1 70.6 93.6 71.0SD 1.4 2.2 3.5 5.5 2.7 3.5

Hearing-impaired R M 63.1 33.4 48.1 20.9 49.3 22.8elderly SD 23.3 18.4 18.4 18.4 22.0 17.2

L M 64.1 28.2 42.0 20.2 43.5 21.9SD 17.4 17.5 18.9 12.4 20.1 12.8

Bin M 70.7 33.0 48.1 30.1 56.9 23.5SD 17.6 20.0 21.0 18.8 20.8 17.7

Normal-hearing, L M 57.2 27.7 46.7 24.9 50.3 26.5simulated SD 5.0 4.7 2.8 3.0 2.6 5.0hearing loss

obtained from the young normal-hearing listeners and theelderly hearing-impaired listeners. The details of theseanalyses are summarized in Table 3. Not surprisingly, asignificant (p < .01) effect of subject group was observedin each of the three analyses. The elderly hearing-im-paired subjects had greater difficulty understandingspeech than the young normal-hearing subjects. Note inFigure 2, however, that the performance of the youngnoise-masked subjects was the same as the elderly hear-ing-impaired subjects across a wide range of conditions.This was confirmed by a separate set of three mixed-

TABLE 3. Summary of analyses of variance performed on thespeech-recognition data from the young normal-hearing andelderly hearing-impaired subjects.

Acousticcondition Effect examined df F

Quiet Group (G) 1, 24 85.99*Reverberation (R) 1, 24 557.51*G x R 1, 24 0.72Listening condition (L) 2, 48 5.46*G x L 2, 48 1.21R x L 2, 48 0.09G x R x L 2, 48 6.41*

Noise at 0° Group (G) 1, 24 86.22*Reverberation (R) 1, 24 516.17*G x R 1, 24 4.64Listening condition (L) 2, 48 9.64*G x L 2, 48 3.95R x L 2, 48 3.79Gx R x L 2, 48 2.78

Noise at 900 Group (G) 1, 24 78.10*Reverberation (R) 1, 24 419.20*G x R 1, 24 0.59Listening condition (L) 2, 48 62.03*G x L 2, 48 45.09*R x L 2, 48 21.96*G x R x L 2, 48 15.10*

*p < .01

design ANOVAs for the two groups with simulated andactual hearing loss for left-ear listening only. These anal-yses are summarized in Table 4. In all three analyses, theeffect of subject group was not significant (p > .05), theeffect of reverberation was significant (p < .01), and thegroup-by-reverberation interaction was not significant(p > .05). These results suggest that the primary factorunderlying the speech recognition difficulties on theelderly hearing-impaired is the presence of a sensorineu-ral hearing loss producing a loss of sensitivity and loud-ness recruitment for high-frequency stimuli. The use ofspectrally shaped masking noise mimics both of theseaspects of sensorineural hearing loss and results in com-parable speech recognition performance.

The effect of simulated hearing loss was only examinedin this study for the left ear. This resulted from twoconsiderations. First, the hearing losses of the hearing-impaired subjects were bilaterally symmetrical, so thatlittle difference in performance was anticipated betweenthe right and left ears for all but the noise-at-900 condi-

TABLE 4. Summary of analyses of variance performed on thespeech-recognition data from the left ears of the young normal-hearing subjects with simulated hearing loss and from elderlyhearing-impaired subjects.

Acousticcondition Effect examined df F

Quiet Group (G) 1, 21 0.8Reverberation (R) 1, 21 259.2*G x R 1, 21 4.2

Noise at 0° Group (G) 1, 21 0.7Reverberation (R) 1, 21 169.1*G x R 1, 21 0.0

Noise at 900 Group (G) 1, 21 0.8Reverberation (R) 1, 21 142.1*G x R 1, 21 0.1

*p < 0.1

33 726-735 December 1990

HUMES & ROBERTS: Speech Recognition by the Elderly 731

tion. Note that the scores of the noise-masked normallisteners (filled diamonds) also provide a reasonable ap-proximation of the right-ear performance of the elderlyhearing-impaired subjects. Second, it was unclear how tosimulate a binaurally symmetrical hearing loss. Changingthe interaural correlation of the noise can cause theperceptual image of the noise to change from a compactcentered intracranial image to a diffuse intracranial imageto two separate intracranial images, one at the right andone at the left (Durlach & Colburn, 1978). We wereuncertain which binaural condition would provide themost faithful simulation of a bilaterally symmetrical hear-ing loss.

Inspection of the data in Figure 2 suggests that theremay be differences in the binaural advantages experi-enced by the young normal-hearing subjects and theelderly hearing-impaired listeners. Note, for instance,that for the young normal-hearing subjects, a differencebetween the performance of the right and left ears existsfor all of the noise conditions, whereas this is never thecase for the elderly listeners. Because the noise wasalways positioned to the right of midline (either 3-4° or90°) while the speech loudspeaker remained fixed at 00azimuth, the left ear received a more favorable signal-to-noise ratio (this was confirmed by direct acoustical mea-surements made with KEMAR at the time experimentaltapes were made). The head effectively shadows thehigh-frequency portions of the noise spectrum, resultingin less noise at the left ear than at the right ear. Thespeech signal, on the other hand, originating at 00 azi-muth, is essentially the same at the two ears. Thus, giventhe acoustic conditions under which the experimentaltapes were produced, one would expect better perfor-mance for the left ear than the right ear when testing innoise. This was clearly observed in the normal youngadults (middle and bottom panels of Figure 2). Theelderly hearing-impaired subjects, however, showed lit-tle interaural difference in speech-recognition perfor-mance. The presence of a high-frequency sensorineuralhearing loss in these listeners rendered the high-fre-quency portions of the speech and noise signals inaudi-ble, thereby negating the improvement in high-frequencysignal-to-noise ratio afforded the normal listeners by thehead shadow. These explanations of the interaural per-formance differences for the normal and impaired sub-jects are consistent with the recent data of Bronkhorst and

Plomp (1988, 1989). It should be noted, moreover, thatthe "binaural" advantage observed in this study for bothgroups of subjects is most often a reflection of the use ofthe ear with the better signal-to-noise ratio and not truebinaural processing of the signals. That is, the score forbinaural listening is generally equivalent to the bestmonaural score obtained in the same acoustic conditions.Binaural release from masking and other forms of binau-ral processing that could potentially improve perfor-mance have their greatest effect at lower frequencies. Theuse of nonsense syllables in this study, for which the highfrequencies contribute more to intelligibility, may havereduced the contributions of true binaural processing tothe observed binaural speech-recognition performance inthis study.

Examination of the speech-recognition scores of indi-vidual hearing-impaired listeners reveals very large dif-ferences in performance among the subjects in this group.Note in Table 2, for instance, that the standard deviationsof the mean data plotted in Figure 2 for the elderlyhearing-impaired subjects are typically 15-20%. Much ofthe individual variability that appears in the speech-recognition performance of the hearing-impaired elderlyis associated with individual differences in audibility.Table 5 contains Pearson r correlation coefficients be-tween speech recognition performance and average hear-ing loss for each of the 18 listening conditions. Themeasure of average hearing loss used was the pure-toneaverage for frequencies of 1000, 2000, and 4000 Hz.Slightly, but consistently, lower correlations were ob-served when the pure-tone average for 500, 1000, and2000 Hz was used. All correlation coefficients in Table 5are strong, negative, and statistically significant (p < .01).In general, these correlations indicate that about 80% ofthe variance in the speech-recognition data of the hear-ing-impaired elderly can be accounted for by variations inaverage hearing loss.

Is the role of hearing loss in speech-recognition perfor-mance effectively captured by acoustical indices such asthe mSTI? To answer this question, octave-band speechand noise levels were measured acoustically with KE-MAR in the anechoic chamber at the time the experimen-tal tapes were generated; reverberation times were mea-sured with the omnidirectional microphone in thereverberation chamber (see Table 1). A noise spectrallyshaped to have a long-term rms octave-band spectrum

TABLE 5. Pearson r correlations between average measures of hearing loss (PTA') and speech-recognition score for the 13 elderly hearing-impaired listeners. All correlations are statisticallysignificant, p < .01.

Acoustic conditionQuiet Noise at 0° Noise at 900

Listening condition T= 0.0 3.1 0.0 3.1 0.0 3.1 s

Right -0.91 -0.93 -0.94 -0.89 -0.88 -0.84Left -0.90 -0.84 -0.85 -0.88 -0.86 -0.81Binaural2 -0.91 -0.89 -0.90 -0.89 -0.90 -0.77

1PTA = pure-tone average for frequencies of 1000, 2000, and 4000 Hz.2Binaural = PTA for left ear plus PTA for right ear, divided by 2.

732 Journal of Speech and Hearing Research

identic;omnidiwas us(noise umeasurmeasurdescribpairedthreshoband nlevelsnoise lescattercorrect)FigurelistenerrepresepilationCUNY

0.00

FIGUREthe octaUnfilledbols reprgles = 1data frorthe eldediamondthe your

al to that of the CUNY NST, as measured with the (Ahlstrom, 1984; Dubno & Levitt, 1981; Humes et al.,rectional microphone in the anechoic chamber, 1986, 1987; Kamm et al., 1985). Octave-band mSTI valuesed to measure the rms speech levels. The cafeteria were calculated for the 246 mean scores obtained fromsed in the speech-recognition testing was used to groups of normal-hearing subjects in these studies, withe the rms noise levels. From these acoustical 5-10 subjects per group. Next, the mSTI continuum wasements, an octave-band mSTI was calculated as divided into bins, .05 in width, from 0.0 to 1.0, and theed by Humes et al. (1986). For the hearing-im- grand means and standard deviations for the set of meanlisteners and the noise-masked normal listeners, NST scores in each bin were calculated. The solid lineld values were converted to equivalent octave- represents the best fit to the grand mean values, and theoise levels using the critical ratio. These noise dashed lines represent the best fits to values two standardwere then added to the acoustically measured deviations above and below the grand means. The bestlevels using linear power summation. The resulting fitting polynomial functions each account for over 98% of)lots of speech-recognition score (in proportion the variance in the mean data and can be considered) by mSTI appear in the top and bottom panels of representative of the expected transfer function between3 for the normal-hearing and hearing-impaired NST score and octave-band mSTI for groups of normal

rs. The solid and dashed lines in both panels listeners.nt best-fitting third-order polynomials fit to a com- Note that the mean data from the normal listeners inl of mean results from several studies that used the this study (top panel) fall within the expected range ofNST to measure speech-recognition performance performance for a given mSTI value. This is true for both

anechoic (unfilled symbols) and reverberant (filled sym-bols) conditions. The speech-recognition scores for bin-aural listening (labeled "both" ears in Figure 3) weresimply plotted at the better-ear mSTI value, which wasalways the left ear for the normal-hearing subjects.

The lower panel of Figure 3 shows an identical scatter-plot for the elderly hearing-impaired listeners. The meanresults from the listeners with simulated loss in the leftear are also plotted in this panel and appear as thediamonds (unfilled and filled). It is clear that the elderlyhearing-impaired listeners perform more poorly than ex-pected for several of the anechoic conditions. Had datanot been obtained from the noise-masked normal listen-ers with simulated hearing loss or the correlational anal-

.O 0.2 0.4 0.6 0.8 1.0 yses not been performed, we might have concluded that

mSTI (octave band) audibility, as captured by the mSTI, was not the primaryfactor determining the speech-recognition performanceof the hearing-impaired elderly. That is, the mSTI, anindex incorporating adjustments for threshold elevation,

----- - overestimates the performance of the elderly hearing-IMPAIRED .. . ..- ' impaired subjects in many conditions. However, the facts

that the young listeners with simulated loss performedlike the elderly hearing-impaired listeners (Figure 2) and

,' /'that both groups of subjects performed more poorly thanpredicted by the mSTI (Figure 3) suggest that the acous-

,' T = 0.0 s 3.1 s tical index is not effectively capturing the contributions of

Rt. O , audibility to the measured speech-recognition perfor-A Lt. L A mance.

x B o t. [ ]A Lt. A * There are several possible reasons that the mSTI usedR/ Both [Z |in this study overestimated the performance of the listen-

/ , . . . , . ers with sloping high-frequency hearing loss, either realD.0 0.2 0.4 0.6 0.8 1.0 or simulated. The use of octave bands, for instance, rather

mSTI (octave band) than ½V-octave bands, may contribute partially to thisproblem (Humes et al., 1986). The manner in which the

3. Mean scores from Figure 2 plotted as a function of acoustically mes et al., 1986). The manner in w hich theve-band modified Speech Transmission Index ( mSTI). acoustically measured noise is combined with the hypo-ve-band modified Speech Transmission Index (mSTI).symbols represent anechoic conditions and filled sym- thetical noise representing quiet threshold may be an-

resent reverberant conditions. Circles = right ear; trian- other more significant factor (Humes, in press). For theeft ear; squares = both ears (binaural). Top panel shows present calculations, recall that a linear power-summa-n normal listeners and bottom panel contains data from tion rule was used to combine the acoustical and hypo-erly hearing-impaired subjects. The filled and unfilled th a a orIs added to the bottom panel represent the scores from thetical noise levels. Whereas this may be appropriate forno listeners with simulated hearing loss. combinations of acoustical noise levels, a nonlinear com-

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33 72-735 December 1990

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HUMES & ROBERTS: Speech Recognition by the Elderly 733

bination rule appears more appropriate for combiningmasked threshold levels (Humes & Jesteadt, 1989). Whenapplying acoustical indices such as the mSTI to thespeech recognition performance of the hearing-impaired,one is required to combine acoustical measurements ofbackground noise with the behavioral measurements ofpure-tone hearing thresholds of the listeners. At least twooptions are available. One approach is to convert thehearing threshold to an equivalent noise level (octave-band level in this study) and then to add it to theacoustically measured background noise levels usinglinear power summation, as would be done with any twoacoustically measured noise levels. This is the traditionalapproach to this problem, and the one used to calculatethe mSTI values shown in Figure 3. A second approachwould be to convert the octave-band levels of the back-ground noise to corresponding masked threshold levelsusing the critical ratio and then combine the two sets ofthresholds: the masked thresholds in the backgroundnoise and the quiet thresholds of the hearing-impaired.Recall that the quiet thresholds can actually be repre-sented as a second set of masked thresholds (Humes,Espinosa-Varas, & Watson, 1988; Dubno & Schaefer,1989). Thus, in this approach, the task becomes one ofcombining two sets of masked thresholds. Humes andJesteadt (1989) have described a nonlinear model that canbe used to perform this task, and its application toacoustical indices such as the AI and the mSTI has beendescribed recently by Humes (in press).

Perhaps the breakdown of the mSTI as a predictor ofthe speech-recognition performance of the hearing-im-paired lies in a complex interaction between the spectraldistortion associated with a high-frequency hearing loss,either real or simulated, and the temporal distortionassociated with reverberation, in a manner consistentwith the suggestions of Lacroix and Harris (1979) andLacroix et al. (1979). Note, however, that the mSTIprovides an excellent description of the performance ofthe normal listeners in reverberant and nonreverberantconditions (Figure 3, top panel). It is the performance ofthe hearing-impaired listeners in the anechoic conditionsthat poses a problem for the mSTI. The failure of themSTI in this study, therefore, cannot be attributed tosome unknown complex interaction between temporaland spectral distortion because the index overestimatesperformance for conditions that did not involve temporaldistortion.

Regardless of the difficulties with the mSTI as a pre-dictor of the performance of the elderly hearing-impaired,it remains the case that the mean speech-recognitiondifficulties of the hearing-impaired elderly were accu-rately simulated by the introduction of a spectrallyshaped masking noise into the ear of young normal-hearing subjects. This spectrally shaped noise producesmasked thresholds that mimic the audiometric contour ofthe hearing-impaired elderly; it also produces loudnessrecruitment. This general finding is consistent with alarge number of recent studies on the psychoacoustic andspeech-recognition performance of young hearing-im-paired listeners, reviewed in the introduction of this

paper, that suggest that an appropriately noise-maskednormal ear provides a good simulation of the performanceof hearing-impaired listeners.

There are some qualifications to this conclusion thatshould be noted. First, all of the hearing-impaired elderlysubjects in this study were between 65 and 75 years old.Whereas the average performance of this particular agegroup may be mimicked by an appropriately shapedmasking noise, this is not necessarily true for everyindividual in this age group or for individuals over age 75.Although the mean speech recognition performance ofthe hearing-impaired elderly was closely approximatelyby the mean performance of the noise-masked normallisteners, much more variability was observed in theolder group (see standard deviations in Table 2). This isdue, in large part, to the approach to simulation pursuedin this study. Specifically, the mean audiogram of thehearing-impaired elderly subjects was simulated in eachof the noise-masked normal listeners, which resulted inmuch less variability than if the individual audiograms ofeach of the hearing-impaired elderly subjects had beensimulated in each of the noise-masked normal listeners.In either of these approaches to simulation, the meanaudiogram of the listeners with simulated loss should bethe same, but the variability associated with the group-matching approach used in this study would be much lessthan that associated with the individual-matching ap-proach. It would be interesting to see whether both themean speech-recognition performance and the variabilityof performance observed in the elderly hearing-impairedsubjects could be simulated using the individual-match-ing approach.

It may also not be possible to generalize the findings ofthe present study beyond the recognition of nonsensesyllables. Nonsense-syllable recognition represents ameasure of speech recognition that would appear to beheavily dependent on acoustical information and periph-eral processing of that information. The recognition ofnonsense syllables, for example, requires no use of se-mantic or syntactic information. Other measures ofspeech recognition, such as the recognition of meaningfulwords, sentences, or continuous discourse, are likely toplace greater demands on central or cognitive resourcesthan nonsense syllables. Speech recognition performancefor these other materials, therefore, may not be as wellaccounted for by the loss of audibility and accompanyingloudness recruitment.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the financial support ofthe National Institutes of Health, the technical support providedby Dave Montgomery and the cheerful participation of thesubjects.

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734 Journal of Speech and Hearing Research

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Received January 17, 1990Accepted May 17, 1990

Requests for reprints should be sent to Larry E. Humes,Indiana University, Audiology Research Laboratory, Depart-ment of Speech and Hearing Sciences, Bloomington, IN 47405.