Word Graph Based Feature Enhancement for Noisy Speech Recognition

Although the existing literature has explored the link between cognitive functioning and speech recognition in noise, the specific role of fluid intelligence still needs to be studied. Given the established association between working memory capacity (WMC) and fluid intelligence and the predictive power of WMC for speech recognition in noise, we aimed to elucidate the mediating role of fluid intelligence. We used data from the n200 study, a longitudinal investigation into aging, hearing ability, and cognitive functioning. We analyzed two age-matched samples: participants with hearing aids and a group with normal hearing. WMC was assessed using the Reading Span task, and fluid intelligence was measured with Raven's Progressive Matrices. Speech recognition in noise was evaluated using Hagerman sentences presented to target 80% speech-reception thresholds in four-talker babble. Data were analyzed using mediation analysis to examine fluid intelligence as a mediator between WMC and speech recognition in noise. We found a partial mediating effect of fluid intelligence on the relationship between WMC and speech recognition in noise, and that hearing status did not moderate this effect. In other words, WMC and fluid intelligence were related, and fluid intelligence partially explained the influence of WMC on speech recognition in noise. This study shows the importance of fluid intelligence in speech recognition in noise, regardless of hearing status. Future research should use other advanced statistical techniques and explore various speech recognition tests and background maskers to deepen our understanding of the interplay between WMC and fluid intelligence in speech recognition.

ObjectivesMany studies have suggested that cochlear implant (CI) users vary in terms of speech recognition in noise. Studies in this field attribute this variety partly to subcortical auditory processing. Studying speech-Auditory Brainstem Response (speech-ABR) provides good information about speech processing; thus, this work was designed to compare speech-ABR components between two groups of CI users with good and poor speech recognition in noise scores. Materials & MethodsThe present study was conducted on two groups of CI users aged 8-10 years old. The first group (CI-good) consisted of 15 children with prelingual CI who had good speech recognition in noise performance. The second group (CI-poor) was matched with the first group, but they had poor speech recognition in noise performance. The speech-ABR test in a sound-field presentation was performed for all the participants. Results The speech-ABR response showed more delay in C, D, E, F, O latencies in CI-poor than CI-good users (P <0.05), meanwhile no significant difference was observed in initial wave (V(t= -0.293, p= 0.771 and A (t= -1.051, p= 0.307). Analysis in spectral-domain showed a weaker representation of fundamental frequency as well as the first formant and high-frequency component of speech stimuli in the CI users with poor auditory performance.ConclusionsResults revealed that CI users who showed poor auditory performance in noise performance had deficits in encoding the periodic portion of speech signals at the brainstem level. Also, this study could be as physiological evidence for poorer pitch processing in CI users with poor speech recognition in noise performance.

Previous research in cochlear implant (CI) recipients with bilateral severe-to-profound sensorineural hearing loss showed improvements in speech recognition in noise using remote wireless microphone systems. However, to our knowledge, no previous studies have addressed the benefit of these systems in CI recipients with single-sided deafness. The objective of this study was to evaluate the potential improvement in speech recognition in noise for distant speakers in single-sided deaf (SSD) CI recipients obtained using the digital remote wireless microphone system, Roger. In addition, we evaluated the potential benefit in normal hearing (NH) participants gained by applying this system. Speech recognition in noise for a distant speaker in different conditions with and without Roger was evaluated with a two-way repeated-measures design in each group, SSD CI recipients, and NH participants. Post hoc analyses were conducted using pairwise comparison t-tests with Bonferroni correction. Eleven adult SSD participants aided with CIs and eleven adult NH participants were included in this study. All participants were assessed in 15 test conditions (5 listening conditions × 3 noise levels) each. The listening conditions for SSD CI recipients included the following: (I) only NH ear and CI turned off, (II) NH ear and CI (turned on), (III) NH ear and CI with Roger 14, (IV) NH ear with Roger Focus and CI, and (V) NH ear with Roger Focus and CI with Roger 14. For the NH participants, five corresponding listening conditions were chosen: (I) only better ear and weaker ear masked, (II) both ears, (III) better ear and weaker ear with Roger Focus, (IV) better ear with Roger Focus and weaker ear, and (V) both ears with Roger Focus. The speech level was fixed at 65 dB(A) at 1 meter from the speech-presenting loudspeaker, yielding a speech level of 56.5 dB(A) at the recipient's head. Noise levels were 55, 65, and 75 dB(A). Digitally altered noise recorded in school classrooms was used as competing noise. Speech recognition was measured in percent correct using the Oldenburg sentence test. In SSD CI recipients, a significant improvement in speech recognition was found for all listening conditions with Roger (III, IV, and V) versus all no-Roger conditions (I and II) at the higher noise levels (65 and 75 dB[A]). NH participants significantly benefited from the application of Roger in noise for higher levels, too. In both groups, no significant difference was detected between any of the different listening conditions at 55 dB(A) competing noise. There was also no significant difference between any of the Roger conditions III, IV, and V across all noise levels. The application of the advanced remote wireless microphone system, Roger, in SSD CI recipients provided significant benefits in speech recognition for distant speakers at higher noise levels. In NH participants, the application of Roger also produced a significant benefit in speech recognition in noise.

Speech recognition of individuals who are listening to a nonnative language is significantly degraded in the presence of background noise and may be influenced by proficiency, age of acquisition, language experience, and daily use of the nonnative language. The purpose of this study is to examine and compare speech recognition in noise performance across test conditions with varying signal-to-noise ratios (SNRs) as well as the presence of vocal and spatial cues in listeners who speak American English as a native language or Mandarin Chinese as a native language. Self-rated English proficiency and experience were collected for native Mandarin Chinese speakers to determine its relationship to performance on the test measures. A cross-sectional repeated measures design was used for the study. Four groups of participants were included in the study. The adult groups consisted of 25 adults who speak native English and 25 adults who speak native Mandarin Chinese with English as an additional language. The pediatric groups consisted of 16 children who speak native English and 16 children who speak native Mandarin Chinese with English as an additional language. Percent correct speech recognition in noise was assessed at three SNRs (-3, 0, +3 dB) using the adult or pediatric versions of the AzBio sentence test. The Listening in Spatialized Noise-Sentence (LiSN-S) test was used to determine the effect of providing spatial and vocal cues on the speech recognition in noise performance of the groups of participants. The data for each age group and test measure were analyzed with a repeated measures analysis of variance. Correlation analyses were performed to examine relationships between English proficiency and experience on performance across the speech recognition test conditions. Analysis of the data from the adult or pediatric AzBio sentence test identified a significant effect of native language for adults but no significant effect for children. The higher SNRs yielded better performance for all listeners. On the LiSN-S test, results for the adult and pediatric groups were similar and showed significantly better performance for the native English speakers in every test condition. The demographic and language characteristics that most affected speech recognition performance across the test measures included the length of time the person lived in the United States, the age of English acquisition, the number of minutes per day English was spoken by the participant, and the self-rated English proficiency. The findings in this study highlight the importance and benefit of higher SNRs as well as the provision of vocal and spatial cues for improving speech recognition performance in noise of adult and pediatric listeners who speak Mandarin Chinese as a native language.

Conclusion. Sequential bilateral implantation offers listening advantages demonstrable on speech recognition in noise and for lateralization. Whilst the trend was for shorter inter-implant intervals and longer implant experience to positively impact binaural advantage, we observed no contraindications for binaural advantage. Objective. To evaluate the benefits of sequential bilateral cochlear implantation over unilateral implantation in a multicentre study evaluating speech recognition in noise and lateralization of sound. Subjects and methods. Twenty children, implanted bilaterally in sequential procedures, had the following characteristics: they were native German-speaking, were3 years or older and had a minimum of 1 year inter-implant interval and had between 2 months and 4 years 7 months binaural listening experience. Binaural advantage was assessed including speech recognition in noise using the Regensburg modification of the Oldenburger Kinder-Reimtest (OLKI) and lateralization of broadband stimuli from three speakers. Results. A significant binaural advantage of 37% was observed for speech recognition in noise. Binaural lateralization ability was statistically superior for the first and second implanted ear (p=0.009, p=0.001, respectively). Binaural experience was shown to correlate moderately with absolute binaural speech recognition scores, with binaural advantage for speech recognition and with binaural lateralization ability. The time interval between implants correlated in an inverse direction with binaural advantage for speech recognition.

&lt;p&gt;Improved cochlear implant (CI) designs and surgical techniques have allowed CI patients to retain acoustic hearing in the implanted ear post-operatively. These EAS (electric-acoustic stimulation) CI users listen with a combination of acoustic and electric hearing in the same ear. While electric hearing alone improves speech recognition in quiet, preserved acoustic hearing allows EAS CI users to outperform traditional CI users in speech recognition in noise and demonstrate “speech masking release,” an improvement in speech recognition in temporally fluctuating noise relative to steady noise. Masking release is arguably an ecologically valid metric, as listeners often attend to target speech embedded in fluctuating competing speech. Improved speech recognition outcomes have been attributed to the spectral and temporal resolution provided by acoustic hearing. However, the relationship between spectral and temporal resolution and outcomes in EAS CI users is not clear.&lt;/p&gt; &lt;p&gt;This study evaluated speech masking release, spectral ripple density discrimination thresholds, and fundamental frequency difference limens (f0DLs) in EAS CI users. Both the ripple and f0DL tasks are thought to measure underlying spectral resolution and temporal fine structure. EAS CI subjects underwent testing in three listening modes: acoustic-only, electric-only, and acoustic+electric. Comparisons across listening modes allowed the benefit provided by acoustic hearing to be quantified.&lt;/p&gt; &lt;p&gt;It was hypothesized that speech masking release, spectral ripple density discrimination thresholds, and f0DLs would be poorest with electric-only hearing and would improve in the acoustic-only and acoustic+electric listening modes. This would reflect the benefit of preserved acoustic hearing. It was also hypothesized that speech masking release would correlate with spectral ripple density discrimination thresholds and f0DLs, reflecting the roles of spectral and temporal fine structure cues. Lastly, it was hypothesized that EAS CI users with more residual hearing (lower audiometric thresholds) would perform better on all three tasks.&lt;/p&gt; &lt;p&gt;Speech masking release was evaluated using a 12-alternative-forced-choice (AFC) spondee recognition in noise task. The noise was a two-talker and a ten-talker babble presented at -5 dB SNR, and masking release was quantified as the difference in spondee recognition in two-talker babble relative to ten-talker babble. Spectral ripple density discrimination thresholds were assessed in a 3-AFC task using a broadband stimulus that contained spectral peaks and valleys logarithmically spaced on the frequency axis. The spacing between spectral peaks (ripple density) was varied to determine the threshold at which listeners could no longer resolve the individual spectral peaks. F0DLs were assessed via a 3-AFC task using a broadband harmonic complex with a baseline f0 = 110 Hz. The f0 of the test intervals was varied to determine the smallest change in f0 that the listener could detect.&lt;/p&gt; &lt;p&gt;Results showed that performance in all three measures was poorest when EAS CI users were tested using electric-hearing only, with significant improvements when tested in the acoustic-only and acoustic+electric listening modes. F0DLs, but not spectral ripple density discrimination thresholds or audiometric thresholds, significantly correlated with speech masking release. Speech masking release also significantly correlated with open-set AzBio sentence recognition in noise scores obtained from clinical records.&lt;/p&gt; &lt;p&gt;Results indicated that preservation of residual acoustic hearing allows for speech masking release, likely due to access to temporal fine structure cues provided by residual hearing. The significant correlation between speech masking release and sentence recognition in noise indicates that the ability to extract target speech embedded in temporally fluctuating competing speech is important for speech recognition in noise.&lt;/p&gt; &lt;p&gt;Funded by National Institutes of Health/National Institutes on Deafness and Other Communication Disorders (NIH/NIDCD) P50 DC000242, American Speech-Language-Hearing Foundation Student Research Grant, and American Academy of Audiology Student Investigator Research Grant.&lt;/p&gt;

While auditory training in quiet has been shown to improve cochlear implant (CI) users' speech understanding in quiet, it is unclear whether training in noise will benefit speech understanding in noise. The present study investigated whether auditory training could improve CI users' speech recognition in noise and whether training with familiar stimuli in an easy listening task (closed-set digit recognition) would improve recognition of unfamiliar stimuli in a more difficult task (open-set sentence recognition). CI users' speech understanding in noise was assessed before, during, and after auditory training with a closed-set recognition task (digits identification) in speech babble. Before training was begun, recognition of digits, Hearing in Noise Test (HINT) sentences, and IEEE sentences presented in steady speech-shaped noise or multitalker speech babble was repeatedly measured to establish a stable estimate of baseline performance. After completing baseline measures, participants trained at home on their personal computers using custom software for approximately 30 mins/day, 5 days/wk, for 4 wks, for a total of 10 hrs of training. Participants were trained only to identify random sequences of three digits presented in speech babble, using a closed-set task. During training, the signal-to-noise ratio was adjusted according to subject performance; auditory and visual feedback was provided. Recognition of digits, HINT sentences, and IEEE sentences in steady noise and speech babble was remeasured after the second and fourth week of training. Training was stopped after the fourth week, and subjects returned to the laboratory 1 mo later for follow-up testing to see whether any training benefits had been retained. Mean results showed that the digit training in babble significantly improved digit recognition in babble (which was trained) and in steady noise (which was not trained). The training benefit generalized to improved HINT and IEEE sentence recognition in both types of noise. Training benefits were largely retained in follow-up measures made 1 mo after training was stopped. The results demonstrated that auditory training in noise significantly improved CI users' speech performance in noise, and that training with simple stimuli using an easy closed-set listening task improved performance with difficult stimuli and a difficult open-set listening task.

The decision to fit one or two hearing aids in individuals with binaural hearing loss has been debated for years. Although some 78% of U.S. hearing aid fittings are binaural (Kochkin , 2010), Walden and Walden (2005) presented data showing that 82% (23 of 28 patients) of their sample obtained significantly better speech recognition in noise scores when wearing one hearing aid as opposed to two. To conduct two new experiments to fuel the monaural/binaural debate. The first experiment was a replication of Walden and Walden (2005), whereas the second experiment examined the use of binaural cues to improve speech recognition in noise. A repeated measures experimental design. Twenty veterans (aged 59-85 yr), with mild to moderately severe binaurally symmetrical hearing loss who wore binaural hearing aids were recruited from the Audiology Department at the Bay Pines VA Healthcare System. Experiment 1 followed the procedures of the Walden and Walden study, where signal-to-noise ratio (SNR) loss was measured using the Quick Speech-in-Noise (QuickSIN) test on participants who were aided with their current hearing aids. Signal and noise were presented in the sound booth at 0° azimuth under five test conditions: (1) right ear aided, (2) left ear aided, (3) both ears aided, (4) right ear aided, left ear plugged, and (5) unaided. The opposite ear in (1) and (2) was left open. In Experiment 2, binaural Knowles Electronics Manikin for Acoustic Research (KEMAR) manikin recordings made in Lou Malnati's pizza restaurant during a busy period provided a typical real-world noise, while prerecorded target sentences were presented through a small loudspeaker located in front of the KEMAR manikin. Subjects listened to the resulting binaural recordings through insert earphones under the following four conditions: (1) binaural, (2) diotic, (3) monaural left, and (4) monaural right. Results of repeated measures ANOVAs demonstrated that the best speech recognition in noise performance was obtained by most participants with both ears aided in Experiment 1 and in the binaural condition in Experiment 2. In both experiments, only 20% of our subjects did better in noise with a single ear, roughly similar to the earlier Jerger et al (1993) finding that 8-10% of elderly hearing aid users preferred one hearing aid.

Objective This study investigated a previously evaluated self-adjustment procedure with respect to its applicability for asymmetrical hearing loss (AHL). Self-adjusted settings were evaluated for speech recognition in noise and sound preference. Design Participants were given the possibility to adjust the left and right hearing aid separately using a two-dimensional user interface. Two different adjustment sequences were tested. Realistic everyday sound scenes in a laboratory environment were presented. The difference between the ears regarding their speech recognition in noise was tested with two spatial conditions, unaided as well as with the prescriptive formula and the self-adjusted setting. Study sample Nineteen experienced hearing aid users (median age 76 years) with different degrees of AHL were invited to participate in this study. Results Participants adjusted a higher gain slope across frequency in the worse ear than in the better one. The two adjustment sequences resulted in significantly different adjustment durations and gain settings. The difference between the ears regarding speech recognition in noise did not change with the self-adjustment. Overall, group-mean effect sizes were small compared to the parameter space. Conclusions The adjustment procedure can be used also by hearing aid users with AHL to find a possibly preferred gain setting.

Speech recognition in noise (SiN) requires explicit cognitive resources such as working memory capacity (WMC). However, existing evidence on the role of WMC in SiN, especially for young adults with normal hearing, is mixed. This study aimed to systematically evaluate the role of WMC when the degree of speech recognition varied as a consequence of adding background noise of varying intensity levels. Specifically, the objective was to determine whether or not there was an effect of noise level on the recruitment of WMC during speech recognition tasks. Fifty-three young adults (18–37 years) with normal hearing were recruited and their ability to recognize speech in the presence of background noise was measured using sentences and words. Speech-to-noise ratios (SNRs) were varied from +10 to −10 dB SNR in 5 dB steps to manipulate the degree of speech recognition. Listeners’ WMC was also measured using two working memory tasks. A significant positive association between WMC and SiN was found for sentence recognition in noise. However, no significant interaction between WMC and SNR was found for isolated word and sentence recognition tasks. WMC was not found to be a significant predictor of word recognition in noise. These results suggests that for young normal hearing listeners, the recruitment of WMC during sentence recognition, especially in non-informational fluctuating noise, is not modulated by the SNR .

Objective: People with presbycusis (PC) often report difficulties in speech recognition, especially under noisy listening conditions. Investigating the PC-related changes in central representations of envelope signals and temporal fine structure (TFS) signals of speech sounds is critical for understanding the mechanism underlying the PC-related deficit in speech recognition. Frequency-following responses (FFRs) to speech stimulation can be used to examine the subcortical encoding of both envelope and TFS speech signals. This study compared FFRs to speech signals between listeners with PC and those with clinically normal hearing (NH) under either quiet or noise-masking conditions.Methods: FFRs to a 170-ms speech syllable /da/ were recorded under either a quiet or noise-masking (with a signal-to-noise ratio (SNR) of 8 dB) condition in 14 older adults with PC and 13 age-matched adults with NH. The envelope (FFRENV) and TFS (FFRTFS) components of FFRs were analyzed separately by adding and subtracting the alternative polarity responses, respectively. Speech recognition in noise was evaluated in each participant.Results: In the quiet condition, compared with the NH group, the PC group exhibited smaller F0 and H3 amplitudes and decreased stimulus-response (S-R) correlation for FFRENV but not for FFRTFS. Both the H2 and H3 amplitudes and the S-R correlation of FFRENV significantly decreased in the noise condition compared with the quiet condition in the NH group but not in the PC group. Moreover, the degree of hearing loss was correlated with noise-induced changes in FFRTFS morphology. Furthermore, the speech-in-noise (SIN) threshold was negatively correlated with the noise-induced change in H2 (for FFRENV) and the S-R correlation for FFRENV in the quiet condition.Conclusion: Audibility affects the subcortical encoding of both envelope and TFS in PC patients. The impaired ability to adjust the balance between the envelope and TFS in the noise condition may be part of the mechanism underlying PC-related deficits in speech recognition in noise. FFRs can predict SIN perception performance.

&lt;p&gt;Objectives: Elementary school classrooms that meet the acoustic requirements for near-optimum speech recognition are extremely scarce. Poor classroom acoustics may become a barrier to speech understanding as children enter school. The purpose of this study was threefold: 1) to quantify the extent to which reverberation, lexical difficulty, and presentation mode affect speech recognition in noise, 2) to examine to what extent auditory-visual (AV) integration assists with the recognition of speech in noisy and reverberant environments typical of elementary school classrooms, 3) to understand the relationship between developing mechanisms of multisensory integration and the concurrently developing linguistic and cognitive abilities.&lt;/p&gt; &lt;p&gt;Design: Twenty-seven typically developing children and 9 young adults participated. Participants repeated short sentences reproduced by 10 speakers on a 30” HDTV and/or over loudspeakers located around the listener in a simulated classroom environment. Signal-to-noise ratio (SNR) for 70 (SNR70) and 30 (SNR30) percent correct performance were measured using an adaptive tracking procedure. Auditory-visual integration was assessed via the SNR difference between AV and auditory-only (AO) conditions, labeled speech-reading benefit (SRB). Linguistic and cognitive aptitude was assessed using the NIH-Toolbox: Cognition Battery (NIH-TB: CB).&lt;/p&gt; &lt;p&gt;Results: Children required more favorable SNRs for equivalent performance when compared to adults. Participants benefited from the reduction in lexical difficulty, and in most cases the reduction in reverberation time. Reverberation affected children’s speech recognition in AO condition and adults in AV condition. At SNR30, SRB was greater than that at SNR70. Adults showed marginally significant increase in AV integration relative to children. Adults also showed increase in SRB for lexically hard versus easy words, at high level of reverberation. Development of linguistic and cognitive aptitude accounts for approximately 35% of the variance in AV integration, with crystalized and fluid cognition composite scores identified as strongest predictors.&lt;/p&gt; &lt;p&gt;Conclusions: The results of this study add to the body of evidence in support of children requiring more favorable SNRs to perform the same speech recognition tasks as adults in simulated listening environments akin to school classrooms. Our findings shed light on the development of AV integration for speech recognition in noise and reverberation during the school years, and provide insight into the balance of cognitive and linguistic underpinnings necessary for AV integration of degraded speech.&lt;/p&gt;

In pure-tone audiometry, hearing thresholds are typically measured up to 8 kHz. Recent research has shown that extended high-frequency (EHF; frequencies >8 kHz) speech information improves speech recognition. However, it is unclear whether the EHF benefit is present for different types of speech material. This study assesses the added value of EHF information for speech recognition in noise for digit triplets, consonant-vowel-consonant (CVC) words, and sentences; and for speech recognition in quiet for CVC. Twenty-four young adults with normal-hearing thresholds up to 16 kHz performed a listening experiment in quiet and in noise in a within-subject repeated measures design. Stimuli were presented monaurally. Steady state speech-shaped noise at a fixed signal to noise ratio was used for measurements in noise. Listening conditions varied only in terms of available EHF information. Stimuli were presented in three different conditions: (1) both speech and noise broadband, (2) speech broadband and noise low-pass filtered at 8 kHz, and (3) both speech and noise low-pass filtered at 8 kHz. In the speech-in-quiet experiment, stimuli (CVC) were high-pass filtered at 3 kHz and presented in two conditions: (1) with EHF information and (2) without EHF information. In the speech-in-noise experiment, for all speech material, the highest scores were achieved in the condition where the noise was low-pass filtered at 8 kHz and speech unfiltered; the lowest scores were obtained in the condition where both speech and noise were low-pass filtered at 8 kHz. Adding speech frequencies above 8 kHz improved the median recognition scores by 75.0%, 21.8%, and 23.8% for digit triplets, words, and sentences, respectively, at a fixed signal to noise ratio. In the speech-in-quiet experiment, median recognition scores were 7.8% higher in the condition where the EHF information was available, as opposed to when it was not. Speech information for frequencies above 8 kHz contributes to speech recognition in noise. It also contributes to speech recognition in quiet when information below 3 kHz is absent. Our results suggest that EHFs may be relevant in challenging listening conditions and should be measured in pure-tone audiometry to get a complete picture of a person's hearing. Further, results of speech recognition tests may vary when different recording and/or measurement equipment is used with different frequency responses above 8 kHz.

Objectives: To determine the effects of different control settings of level-dependent hearing protectors on speech recognition performance in interaction with hearing loss. Design: Controlled laboratory experiment with two level-dependent devices (Peltor® PowerCom Plus™ and Nacre QuietPro®) in two military noises. Study sample: Word recognition scores were collected in protected and unprotected conditions for 45 participants grouped into four hearing profile categories ranging from within normal limits to moderate-to-severe hearing loss. Results: When the level-dependent mode was switched off to simulate conventional hearing protection, there were large differences across hearing profile categories regarding the effects of wearing the devices on speech recognition in noise; participants with normal hearing showed little effect while participants in the most hearing-impaired category showed large decrements in scores compared to unprotected listening. Activating the level-dependent mode of the devices produced large speech recognition benefits over the passive mode at both low and high gain pass-through settings. The category of participants with the most impaired hearing benefitted the most from the level-dependent mode. Conclusions: The findings indicate that level-dependent hearing protection circuitry can provide substantial benefits in speech recognition performance in noise, compared to conventional passive protection, for individuals covering a wide range of hearing losses.

Even older adults with relatively mild hearing loss report hearing handicap, suggesting that hearing handicap is not completely explained by reduced speech audibility. We examined the extent to which self-assessed ratings of hearing handicap using the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) were significantly associated with measures of speech recognition in noise that controlled for differences in speech audibility. One hundred sixty-two middle-aged and older adults had HHIE total scores that were significantly associated with audibility-adjusted measures of speech recognition for low-context but not high-context sentences. These findings were driven by HHIE items involving negative feelings related to communication difficulties that also captured variance in subjective ratings of effort and frustration that predicted speech recognition. The average pure-tone threshold accounted for some of the variance in the association between the HHIE and audibility-adjusted speech recognition, suggesting an effect of central and peripheral auditory system decline related to elevated thresholds. The accumulation of difficult listening experiences appears to produce a self-assessment of hearing handicap resulting from (a) reduced audibility of stimuli, (b) declines in the central and peripheral auditory system function, and (c) additional individual variation in central nervous system function.