Trends in Hearing最新文献

This study investigated the effect of temporal misalignment between acoustic and simulated electric signals on the ability to process fast speech in normal-hearing listeners. The within-ear integration of acoustic and electric hearing was simulated, mimicking the electric-acoustic stimulation (EAS) condition, where cochlear implant users receive acoustic input at low frequencies and electric stimulation at high frequencies in the same ear. Time-compression thresholds (TCTs), defined as the 50% correct performance for time-compressed sentences, were adaptively measured in quiet and in speech-spectrum noise (SSN) as well as amplitude-modulated noise (AMN) at 4 dB and 10 dB signal-to-noise ratio (SNR). Temporal misalignment was introduced by delaying the acoustic or the simulated electric signals, which were generated using a low-pass filter (cutoff frequency: 600 Hz) and a five-channel noise vocoder, respectively. Listeners showed significant benefits from the addition of low-frequency acoustic signals in terms of TCTs, regardless of temporal misalignment. Within the range from 0 ms to ±30 ms, temporal misalignment decreased listeners' TCTs, and its effect interacted with SNR such that the adverse impact of misalignment was more pronounced at higher SNR levels. When misalignment was limited to within ±7 ms, which is closer to the clinically relevant range, its effect disappeared. In conclusion, while temporal misalignment negatively affects the ability of listeners with simulated EAS hearing to process fast sentences in Mandarin, its effect is negligible when it is close to a clinically relevant range. Future research should validate these findings in real EAS users.

Hearing aids have traditionally been designed to facilitate speech perception. With regards to music perception, previous work indicates that hearing aid users frequently complain about music sound quality. Yet, the effects of hearing aid amplification on musical perception abilities are largely unknown. This study aimed to investigate the effects of hearing aid amplification and dynamic range compression (DRC) settings on musical scene analysis (MSA) abilities and sound quality ratings (SQR) using polyphonic music recordings. Additionally, speech reception thresholds in noise (SRT) were measured. Thirty-three hearing aid users with moderate to severe hearing loss participated in three conditions: unaided, and aided with either slow or fast DRC settings. Overall, MSA abilities, SQR and SRT significantly improved with the use of hearing aids compared to the unaided condition. Yet, differences were observed regarding the choice of compression settings. Fast DRC led to better MSA performance, reflecting enhanced selective listening in musical mixtures, while slow DRC elicited more favorable SQR. Despite these improvements, variability in amplification benefit across DRC settings and tasks remained considerable, with some individuals showing limited or no improvement. These findings highlight a trade-off between scene transparency (indexed by MSA) and perceived sound quality, with individual differences emerging as a key factor in shaping amplification outcomes. Our results underscore the potential benefits of hearing aids for music perception and indicate the need for personalized fitting strategies tailored to task-specific demands.

When listening to speech under adverse conditions, listeners compensate using neurocognitive resources. A clinically relevant form of adverse listening is listening through a cochlear implant (CI), which provides a spectrally degraded signal. CI listening is often simulated through noise-vocoding. This study investigated the neurocognitive mechanisms supporting recognition of spectrally degraded speech in adult CI users and normal-hearing (NH) peers listening to noise-vocoded speech, with the hypothesis that an overlapping set of neurocognitive functions would contribute to speech recognition in both groups. Ninety-seven adults with either a CI (54 CI individuals, mean age 66.6 years, range 45-87 years) or age-normal hearing (43 NH individuals, mean age 66.8 years, range 50-81 years) participated. Listeners heard materials varying in linguistic complexity consisting of isolated words, meaningful sentences, anomalous sentences, high-variability sentences, and audiovisually (AV) presented sentences. Participants were also tested for vocabulary knowledge, nonverbal reasoning, working memory capacity, inhibition-concentration, and speed of lexical and phonological access. Linear regression analyses with robust standard errors were performed for speech recognition tasks on neurocognitive functions. Nonverbal reasoning contributed to meaningful sentence recognition in NH peers and anomalous sentence recognition in CI users. Speed of lexical access contributed to performance on most speech tasks for CI users but not for NH peers. Finally, inhibition-concentration and vocabulary knowledge contributed to AV sentence recognition in NH listeners alone. Findings suggest that the complexity of speech materials may determine the particular contributions of neurocognitive skills, and that NH processing of noise-vocoded speech may not represent how CI listeners process speech.

Localization of sound sources in sagittal planes significantly relies on monaural spectral cues. These cues are primarily derived from the direction-specific filtering of the pinnae. The contribution of specific frequency regions to the cue evaluation has not been fully clarified. To this end, we analyzed how different spectral weighting schemes contribute to the explanatory power of a sagittal-plane localization model in response to wideband, flat-spectrum stimuli. Each weighting scheme emphasized the contribution of spectral cues within well-defined frequency bands, enabling us to assess their impact on the predictions of individual patterns of localization responses. By means of Bayesian model selection, we compared five model variants representing various spectral weights. Our results indicate a preference for the weighting schemes emphasizing the contribution of frequencies above 8 kHz, suggesting that, in the auditory system, spectral cue evaluation is upweighted in that frequency region. While various potential explanations are discussed, we conclude that special attention should be put on this high-frequency region in spatial-audio applications aiming at the best localization performance.

Understanding speech among competing speech poses a substantial challenge. In these environments, familiar voices-including naturally familiar (e.g., friends, partners) and lab-trained voices-are more intelligible than unfamiliar voices. Yet, whether familiar voices also require less effort to understand is currently unknown. We trained 20 participants to become familiar with three voices, then tested listening effort during a speech intelligibility task. During familiarization and training, participants were exposed to three talkers for different lengths of time, either speaking 88, 166, or 478 sentences ("Least Familiar," "Moderately Familiar," or "Most Familiar" voice, respectively). During each trial of the speech intelligibility task, two competing sentences were presented at a target-to-masker ratio (TMR) of -6 or +3 dB. Participants reported target sentences that were spoken by trained or by novel, unfamiliar talkers. We assessed effort using self-reported ratings and physiologically, using pupil dilation. We found that self-report scores were more sensitive than pupil dilation to differences in TMR, with lower self-reported effort at +3 than -6 dB TMR. The two measures may also be differentially sensitive to the extent of training. We found lower self-reported effort for all three trained voices over unfamiliar voices, with no differences among the trained voices, whereas pupil dilation was only lower for the voice that had been trained for the longest. Thus, both self-report scores and pupil dilation showed advantages for the voice that was trained for the longest (∼1 h), but self-report scores additionally showed reduced effort even following relatively short durations of training (<10 min).

Age-related hearing loss (ARHL) currently affects over 20 million adults in the U.S. and its prevalence is expected to increase as the population ages. However, little is known about the earliest manifestations of ARHL, including its influence on auditory function beyond the threshold of sensation. This work explores the effects of early aging on frequency selectivity (i.e., "tuning"), a critical feature of normal hearing function. Tuning is estimated using both behavioral and physiological measures-fast psychophysical tuning curves (fPTC), distortion product otoacoustic emission level ratio functions (DPOAE LRFs), and stimulus-frequency OAE (SFOAE) phase gradient delay. All three measures were selected because they have high potential for clinical translation but have not been compared directly in the same sample of ears. Results indicate that there may be subtle changes in tuning during early aging, even in ears with clinically normal audiometric thresholds. Additionally, there are notable differences in tuning estimates derived from the three measures. Psychophysical tuning estimates are highly variable and statistically significantly different from OAE-derived tuning estimates, suggesting that behavioral tuning is uniquely influenced by factors not affecting OAE-based tuning. Across all measures, there is considerable individual variability that warrants future investigation. Collectively, this work suggests that age-related auditory decline begins in relatively young ears (<60 years) and in the absence of traditionally defined "hearing loss." These findings suggest the potential benefit of characterizing ARHL beyond threshold and establishing a gold standard for measuring frequency selectivity in humans.

In addition to speech intelligibility, listening effort has emerged as a critical indicator of hearing performance. It can be defined as the effort experienced or invested in solving an auditory task. Subjective, behavioral, and physiological methods have been employed to assess listening effort. While previous studies have focused predominantly evaluated listening effort at clearly audible levels, such as in speech-in-noise conditions, we present findings from a study investigating listening effort for soft speech in quiet. Twenty young adults with normal hearing participated in speech intelligibility testing (OLSA), adaptive listening effort scaling (ACALES), and pupillometry. Experienced effort decreased with increasing speech level and "no effort" was reached at 40 dB sound pressure level (SPL). The difference between levels rated with "extreme effort" and "no effort" was, on average, 20.6 dB SPL. Thus, speech must be presented well above the speech-recognition threshold in quiet to achieve effortless listening. These results prompted a follow-up experiment involving 18 additional participants, who completed OLSA and ACALES tests with hearing threshold-simulating noise at conversational levels. Comparing the results of the main and follow-up experiments suggests that the observations in quiet cannot be fully attributed to the masking effects of internal noise but likely also reflect cognitive processes that are not yet fully understood. These findings have important implications, particularly regarding the benefits of amplification for soft sounds. We propose that the concept of a threshold for effortless listening has been overlooked and should be prioritized in future research, especially in the context of soft speech in quiet environments.

Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highest comfortable level of the listener, while noise reduction reduces ambient noise with the goal of improving intelligibility and listening comfort and reducing effort. In most current hearing aids, noise reduction and WDRC are implemented sequentially, but this may lead to distortion of the amplitude modulation patterns of both the speech and the noise. This paper describes a deep learning method, called Neural-WDRC, for implementing both noise reduction and WDRC, employing a two-stage low-complexity network. The network initially estimates the noise alone and the speech alone. Fast-acting compression is applied to the estimated speech and slow-acting compression to the estimated noise, but with a controllable residual noise level to help the user to perceive natural environmental sounds. Neural-WDRC is frame-based, and the output of the current frame is determined only by the current and preceding frames. Neural-WDRC was compared with conventional slow- and fast-acting compression and with signal-to-noise ratio (SNR)-aware compression using objective measures and listening tests based on normal-hearing participants listening to signals processed to simulate the effects of hearing loss and hearing-impaired participants. The objective measures demonstrated that Neural-WDRC effectively reduced negative interactions of speech and noise in highly non-stationary noise scenarios. The listening tests showed that Neural-WDRC was preferred over the other compression methods for speech in non-stationary noises.

This study investigated which of a range of factors could explain performance in two distinct groups of experienced, adult cochlear implant recipients differentiated by performance on words in quiet: 72 with poorer word scores versus 77 with better word scores. Tests measured the potential contribution of sound processor mapping, electrode placement, neural health, impedance, cognitive, and patient-related factors in predicting performance. A systematically measured sound processor MAP was compared to the subject's walk-in MAP. Electrode placement included modiolar distance, basal and apical insertion angle, and presence of scalar translocation. Neural health measurements included bipolar thresholds, polarity effect using asymmetrical pulses, and evoked compound action potential (ECAP) measures such as the interphase gap (IPG) effect, total refractory time, and panoramic ECAP. Impedance measurements included trans impedance matrix and four-point impedance. Cognitive tests comprised vocabulary ability, the Stroop test, and the Symbol Digits Modality Test. Performance was measured with words in quiet and sentence in noise tests and basic auditory sensitivity measures including phoneme discrimination in noise and quiet, amplitude modulation detection thresholds and quick spectral modulation detection. A range of predictor variables accounted for between 33% and 60% of the variability in performance outcomes. Multivariable regression analyses showed four key factors that were consistently predictive of poorer performance across several outcomes: substantially underfitted sound processor MAP thresholds, higher average bipolar thresholds, greater total refractory time, and greater IPG offset. Scalar translocation, cognitive variables, and other patient related factors were also significant predictors across more than one performance outcome.

This study investigates the impact of hearing aid (HA) use on visual lexical decision (LD) performance in individuals with hearing loss. We hypothesize that HA use benefits phonological processing and leads to faster and more accurate visual LD. We compared the visual LD performance among three groups: 92 short-term HA users (<5 years), 98 long-term HA users, and 55 nonusers, while controlling for hearing level, age, and years of education. Results showed that, compared with non-HA users, HA users showed significantly faster reaction times in visual LD, specifically, long-term HA use was associated with smaller difference in reaction time for pseudowords compared to nonwords. These results suggest that HA use is associated with faster visual word recognition, potentially reflecting enhanced cognitive functions beyond auditory processing. These findings point to possible cognitive advantages linked to HA use.