J Am Acad Audiol 2 : 146-150 (1991) Speech Recognition in Noise for Hearing- Impaired Subjects : Effects of an Adaptive Filter Hearing Aid Carl R. Chiasson* Robert 1. Davis* Abstract Speech-recognition thresholds (SRTs) were obtained in nine sensorineural hearing-impaired subjects wearing an adaptive-filter hearing aid under four separate listening conditions. The SRT was obtained with the filter in and out of the circuit in order to relate the effects of noise reduction to speech recognition performance. The noise level was held constant while the speech level varied (transformed up-down method). For the majority of the subjects tested, the activation of the noise-suppression circuit in the aid resulted in performance equivalent to or worse than that obtained without the circuit activated. For the group, a significant improvement (< 0.05) in recognition was observed only in low-frequency noise competition. Key Words : Adaptive filter, ZETA aid, hearing aids, speech recognition earing aids using self-adaptive filtering techniques have been developed as a means to help improve the H speech-recognition performance of hearing-impaired individuals. The results of some investigations with hearing-impaired subjects listening in various noise competitions suggest that such hearing aids are beneficial and superior to conventional linear hearing aids (Stein and Dempesy-Hart, 1984 ; Wolinsky, 1986 ; Stein et al, 1989 ; Chiasson and Davis, 1990 ; Schum, 1990). Other studies, however, have found little or no advantage associated with the adaptive instruments. Van Tasell et al (1988), for instance, obtained aided speech reception thresholds (SRTs) for six hearing-impaired adults in noise (speechspectrum and low-frequency) with a master hearing aid incorporating the zeta noise block (ZNB). With the ZNB on, lower SRTs occurred for monosyllables in low-frequency noise, while 'S.U.N.Y. at Plattsburgh, Hearing and Speech Science Department, Plattsburgh, New York Reprint requests : Robert I. Davis, S.U.N.Y. at Plattsburgh, Hearing and Speech Science Department, Plattsburgh, NY 12901 higher (worse) SRTs occurred for the spondees in broadband noise. In addition, Klein (1989) examined speech-recognition performance for spondees in noise in six normal-hearing and five hearing-impaired subjects wearing a ZNB hearing aid with the processor turned on and off. Although results varied widely, there was a trend toward equivalent performance between a conventional hearing aid and one with the ZNB activated. Finally, Tyler and Kuk (1989) measured consonant recognition (/i/-consonant- /i/) in the presence of speech-babble noise and in low-frequency noise (100-800 Hz, roll off = 115 db/octave) in 16 hearing-impaired subjects. Seven different "noise suppression" hearing aids were assessed with each subject. The authors concluded that the hearing aids "were not very effective in improving consonant recognition in the presence of background noise" (p. 247). Some subjects demonstrated better performance while most showed either no difference or worse performance with the processing circuit activated. On the basis of these studies, it appears that the effectiveness of digitally controlled adaptive filters in minimizing the deleterious effects of background noise on recognition performance remains equivocal. To a certain extent, the discrepancies among researchers can 146
Adaptive Filter on Speech Recognition/Chiasson and Davis be attributed to the variety of experimental designs employed to assess performance, (single-subject design, Stein et al, 1989 ; groupsubject design, Klein, 1989 ; Van Tasell et al, 1988 ; Tyler and Kuk,1989), the various degrees and configurations of hearing loss, the number of subjects tested, and the manner in which the frequency response of the hearing aid was optimized. The discrepancy of results obtained with adaptive filtering requires that investigations utilize a reliable measure of performance in a wide variety of competitions. The speech recognition threshold (SRT) for spondees is useful in this regard since it is more reliable than a 50-word recognition score for monosyllables, and it provides a straightforward test of the adaptive filter and other noise reduction systems (Van Tasell et al, 1988). However, the speech material often used to assess listener performance in competition with the adaptivefilter hearing aids has been NU-6 word lists (Stein and Dempesy-Hart, 1984 ; Wolinsky,1986 ; Dempesy,1987), the Synthetic Sentence Identification (Stach et al, 1987), or the Speech Perception in Noise Test (Stein et al, 1989). The application of these more commonly applied clinical test techniques provides a potential advantage for use in the clinical setting to mine if one can benefit from noise suppression aids. Before determining who can benefit, however, one must first determine if noise suppression hearing aids provide a distinct and consistent advantage over traditional automatic gain control or high-pass filter hearing aids. To this end, we decided to utilize the SRT, which reflects the interfering effect of noise on speech (Hirsh and Bowman, 1953) to determine the degree to which interference is reduced by the adaptive filter. Another potential problem involves the nonoptimal frequency response of the hearing aid that can result when subjects are allowed to adjust the volume control separately in noise for filter-in and filter-out conditions (e.g., Stein and Dempesy-Hart, 1984 ; Wolinsky,1986 ; Tyler and Kuk, 1989). This can result in a compensatory effect on the amount of attenuation provided by the adaptive filter unless the volume control is held constant. Since both practices are justifiable (e.g., adjust or not adjust gain in different noises and/or with the filter in and out), it is necessary to present a rationale for selecting the approach used as it relates to the specific goals of the study as Tyler and Kuk did (e.g., assess realistic listening performance of hearing aid user). Since we wanted to assess the relation of the speech and competition spectra on task performance, the volume control of the hearing aid was held constant within each test session. This allows for a more precise interpretation ofthe effectiveness ofthe adaptive filter's ability to enhance the signal-to-noise ratio by attenuating frequency regions within and remote from the speech spectrum (spondees). Speech-recognition performance in hearing-impaired subjects was compared in several noise competitions using a custom in-the-ear hearing aid with the self-adaptive filter in and out of the circuit. We attempted to make performance comparisons (filter in and out) using a group experimental design that employs two realistic (babble and cafeteria noise) and two noise (low-frequency and speech spectrum) competitions. The frequency spectra of the competitions and the stimuli to be recognized (spondees) were related to task performance with the noise reduction hearing aid (adaptive filter). We considered that a significant improvement in performance with the filter circuit-in for certain competitions would provide evidence to support its application for use in similar environmental listening situations. Subjects METHOD Nine subjects with sensorineural hearing loss (age range 47 to 68 years ; mean age 57 years) participated in the experiment. Peripheral sensitivity loss (average of HTLs at 500, 1000, and 2000 Hz) in this group varied from mild (three subjects), to moderate (four subjects), to moderately severe (two subjects) hearing loss. All subjects were experienced hearing aid wearers (i.e., linear amplifiers) for at least 10 years. Impedance testing revealed normal middle-ear function. No subject in any group showed evidence by history or test results (suprathreshold adaptation test, acoustic reflex testing) of retrocochlear involvement. The audiometric data for each individual subject are shown in Table 1. Procedures Preliminary audiometric evaluation consisted of pure-tone, speech-recognition threshold, word-recognition, and impedance testing (tympanometry, acoustic reflex tests). During testing, the nontest ear of each subject was occluded with a neoprene insert. Subjects ad- 147
Journal of the American Academy of Audiology/Volume 2, Number 3, July 1991 Table 1 Pure-Tone Air-Conduction (db HL), Speech-Recognition Thresholds (SRTs), and Word-Recognition (WR) Scores for Hearing-Impaired Subjects (Test Ear) Subject 0.25 0.5 1.0 Frequency (khz) 2.0 3.0 4.0 8.0 SRT (db HL) 1 45 40 60 70 65 65 85 50 76 2 50 50 45 50 55 60 90 48 52 3 10 30 35 45 40 35 25 33 80 4 45 45 60 65 60 60 75 52 76 5 40 45 50 50 45 40 60 48 96 6 5 10 55 85 85 80 90 35 48 7 15 15 10 35 60 80 70 15 84 8 15 10 5 55 55 55 30 15 84 9 35 35 40 75 75 80 100 43 72 WR M justed the volume control of a custom in-the-ear hearing aid (Starkey CE-7) once to an audio tape of continuous discourse presented at 62 db SPL in quiet until the most comfortable listening level (MCL) was obtained with the filter out. Thus, we focused on the specific response of the filter at MCL (one setting that was held constant) as opposed to evaluating how the hearing aid might function in everyday use (different gain control settings). The filter-off frequency response of each subject's hearing aid was determined on the basis of the NAL-revised prescriptive procedure (Bryne and Dillon, 1986). Hearing aids provided by the manufacturer matched specifications (2cc full-on coupler gain across frequency, 250-1000 Hz) that were within ± 4 db of the NAL procedure. Hearing aids exceeding this criteria were excluded. A different custom hearing aid was individually fitted in each subject. All testing was performed in a double-walled test chamber (IAC 1204A). All speech (list of 16 homogeneous spondees) and competitive stimuli (speech, cafeteria, multitalker, and a 750-Hz narrowband noise) were produced from tapes supplied by Auditec of St. Louis and routed from a cassette tape deck (Sharp RT-20) to a twochannel audiometer (Grason Stadler 10) and booster amplifier. The speech noise was generated by the audiometer. The spondees used in this study were selected on the basis of their familiarity and similarity of threshold levels (Klein, 1989). Primary and competing stimuli were presented from one loudspeaker at 0 azimuth and 1 m from the center of the subject's head. The average (RMS) sound pressure level of the spondees (± 2 db) and all competitive stimuli were individually analyzed in one-third octave bands at the location of the subject's head with a precision sound level meter (Larson- Davis model 800B), and are shown in Figure 1. Frequency (khz) Figure 1 Average (rms) sound pressure level in onethird octave bands for spondees and each competition at an overall level of 62 db SPL. Below 800 Hz the spondees contained less energy than all types of competition, except for the 750-Hz narrowband noise. From 1250 Hz to 2500 Hz the spondees contained more energy than the narrowband and cafeteria noises and less energy than the speech- and multitalkernoise competitions. From above 2500 Hz to approximately 5000 Hz the spondees were more intense than all competitions, except the speech noise. The spondees and noise levels were initially set at 62 db SPL and averaged at 0 db on the VU meter of the audiometer. Calibration signals (speech noise) in the speech (spondees) and noise (competitions) channels were equal in level to the average SPL of the speech and competing noise presented at the location of the subject's head. This level ensured the activation of the noise-suppression circuit of the hearing aid (i.e., exceeded the noise threshold of the chip in the hearing aid). A transformed up-down method (Levitt, 1971) was used to determine the 50 percent 1o 148
Adaptive Filter on Speech Recognition/Chiasson and Davis performance-intensity level for each of the four listening conditions. Initially, the first six spondees were presented between 65-75 db SPL (to determine "ceiling" area) after which the speech intensity was increased after each incorrect response and reduced after each correct response in 8-dB steps. After two reversals, the step size was reduced to 1 db and testing continued until 14 reversals had occurred. The mean and standard deviation of the stimulus presentation levels corresponding to the final 7 reversals was calculated ; the mean was taken as threshold estimate for that experimental run. Each SRT estimate was the mean of the threshold estimates from two experimental runs. Data from runs with standard deviations greater than 3 db were excluded. For each subject, a practice run was completed prior to testing. The SRT was obtained in a randomized manner for each test condition : unaided, filter in, and filter out (linear) in each of the four background noises. Judgments as to whether or not a response was correct were made by an independent observer who was unaware of the status of the hearing aid (filter in versus filter out). RESULTS able 2 illustrates the difference, in db, T between the aided filter-out versus filter-in SRT values for each subject under each competition condition. A negative number denotes a higher SRT (i.e., poorer performance) with the filter in. A one-way analysis of variance design (single-factor analysis with repeated measures) was performed on these data under each competition to assess the effect of the adaptive filter hearing aid as a function of noise competition. The F ratio for the main effect of noise condition (SRT difference scores between listening conditions) was significant, F (3,24) = 9.39, p < 0.05. A Tukey's test was performed to identify which listening conditions were significantly different (0.05 level) from each other. The results showed that the mean difference with the filter in and filter out was significantly larger (improvement in SRT) for low-frequency noise. There were no significant differences among any of the other competition comparisons (cafeteria versus multitalker or speech noise, and multitalker versus speech noise). The result of t-tests (two tailed) also revealed similar effects (p < 0.05) when the absolute SRT scores were compared between noise competitions. Also, there was a small but systematic effect on the mean SRT difference (filter out minus filter in) as the competition changed from speech noise (0.77 db) to multitalker babble (1.47 db) to cafeteria noise (1.58 db) and low-frequency noise (2.74 db). Thus, the speech noise was the most effective masker, while the low-frequency noise (not surprisingly) was the least effective masker. This systematic result can be accounted for by the degree of midfrequency energy contained in each competition and its relative effectiveness for masking the spondees (see Fig. 1). W DISCUSSION ith the increasing variety of studies designed to evaluate the effectiveness of adaptive filter hearing aids and the discrepancy Table 2 Difference for (Filter Out minus Filter In) in Speech-Recogni tion Threshold (db SPL) Spondees in Four Types of Background Com petition Subject Low Frequency Speech Cafeteria Multitalker Combined Standard Noise Spectrum Noise Mean Deviation Noise 1 6.8 5.6` 7.8 7.7" 6.98' 1.0 2-0.2 1.2-0.4 0.1 0.18 0.7 3 0.5-1.0-1.3 0.4-0.35 0.9 4 5.8 0.7 1.2 3.1 1.2 3.7 5 0.9-0.6 10.1' 5.0 3.9 4.8 6 5.2 3.0 3.5 1.7 3.1 1.5 7 2.3-1.9-1.4 1.1 0.03 2.0 8 2.1-2.5-0.8 1.3 0.1 2.1 9 1.3 2.4-3.5-1.0-0.2 2.6 x 2.74 0.77 1.58 1.47 1.66 0.8 SD 2.4 2.4 4.3 3.0 2.3 'exceeds 2 standard deviations relative to mean threshold difference within that competition. -= poorer performance for filter-in condition. 149
Journal of the American Academy of Audiology/Volume 2, Number 3, July 1991 of findings reported, the clinician is still faced with the difficulty of trying to determine if a noise suppression hearing aid is best for a particular patient. From our group results, it appears that optimal speech recognition in different types of noise will occur with noise suppression or linear amplifiers. The results presented in this paper, for instance, show a systematic relation between the spectra of energy of a background noise and the degree of benefit received from the adaptive filter hearing aid. Since results varied widely (e.g., some showed no change or poorer performance with the filter in) both within and between subjects across noise competitions and for all competition values when combined, it is clear that optimal benefit from a noise suppression aid is not guaranteed. This result is consistent with previous findings (Klein, 1989 ; Tyler and Kuk, 1989). There is clear evidence, however, that for some individuals noise suppression devices are superior to conventional hearing aids (Wolinsky, 1986 ; Stein and Dempesy-Hart, 1984 ; Schum, 1990 ; Chiasson and Davis, 1990). Detectable improvement in performance with the adaptive filter in was also observed in a few subjects in this report (see Table 2). In general, however, our results suggest that the adaptive filter hearing aid used in this study did not consistently provide the optimum benefit desired from an aid that is designed to enhance the S/N when the spectrum of the noise and speech considerably overlap. The only exception is when speech recognition occurs in low-frequency noise. Even in this case, however, improvement in performance is not assured. To a large extent, the inconsistent performance observed in all competitions except for the 750-Hz narrowband noise can be explained by the relations among the stimulus band levels shown in Figure 1. Consistent with previous reports by Van Tasell et al (1988) and Klein (1989), improvement in recognition is more likely to occur when the speech and noise spectra do not overlap (e.g., low-frequency noise) and less likely when the spectra do overlap (e.g., spondees with cafeteria, multitalker and speech noise). Also, since the spectrum of the background noise influences the frequency response of the adaptive filter, the hearing aid's frequency response in noise may have been more appropriate for some hearing-impaired subjects than for others. We have demonstrated that group results show no clear agreement between the effectiveness of the noise suppression hearing aid and recognition performance in three of the four noise competitions employed in this study. Thus, hearing health care providers must be aware of the variability in success with noise suppression hearing aids and must therefore apply caution in advocating its routine application for those seeking a solution to the problem of speech recognition in noise. REFERENCES Bryne DJ, Dillon H. (1986). The National Acoustic Laboratories (NAL) new procedure for selecting the gain and frequency response of a hearing aid. Ear Hear 7:257-265. Chiasson CR, Davis R1. (1990). A comparison of adaptive signal processing and high pass filter hearing aids on speech recognition in normal and sensorineural ears. Hear Instruments 44 :28-31. Dempesy J. (1987). Effect of automatic signal-processing amplification on speech-recognition in noise for persons with sensorineural hearing loss. Ann Otol Rhinol Laryngol 96 :251-253. Hirsh IJ, Bowman WD. (1953). Masking of speech by bands of noise. J Acoust Soc Am 25:1175-1180. Klein AJ. (1989). Assessing speech recognition in noise for listeners with a signal processor hearing aid. Ear Hear 10:50-57. Levitt H. (1971). Transformed up-down methods in psychoacoustics. J Acoust Soc Am 49 :467-477. Schum DJ. (1990). Noise reduction strategies for elderly, hearing-impaired listeners. J Am Acad Audiol 1:31-36. Stach B, Speerschneider J, Jerger J. (1987). Evaluating the efficacy of automatic signal processing hearing aids. Hear J 40 :15-19. Stein LK, Dempesy-Hart D. (1984). Listener-assessed intelligibility of a hearing aid self-adaptive noise filter. Ear Hear 5:199-204. Stein LK, McGee T, Lewis P. (1989). Speech recognition measures with noise suppression hearing aids using a single-subject experimental design. Ear Hear 10 :6, 375-381. Tyler RS, Kuk FK. (1989). The effects of "noise suppression" hearing aids on consonant recognition in speechbabble and low-frequency noise. Ear Hear 10:243-249. Van Tasell DJ, Larsen SY, Fabry DA. (1988). Effects of an adaptive filter hearing aid on speech recognition in noise by hearing-impaired subjects. Ear Hear 9:15-21. Wolinsky S. (1986). Clinical assessment of a self-adaptive noise filtering system. Hear J 39 :29-32. 150