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Hearing loss is a highly prevalent chronic condition that degrades the quality of life. Although hearing aids provide immediate and efficient benefits to listeners with mild-to-moderate hearing loss, the prevalence of hearing aid use has been low. Consumer wireless earbuds are increasingly being equipped with the ability to amplify external sounds, which can be an affordable alternative to hearing aids. This study compared the amplification performance of non-customized Bluetooth consumer hearables to high-end hearing aids when used by people with mild-to-moderate hearing loss. We found that such a non-customized consumer device significantly enhances the speech recognition of listeners with mild-to-moderate hearing loss, although its performance did not reach the hearing aids. These results determine the extent to which inexpensive and accessible non-customized Bluetooth hearables can help people with mild-to-moderate hearing loss.

Auditory selective attention is a crucial top-down cognitive mechanism for understanding speech in noise. Cochlear implant (CI) users display great variability in speech-in-noise performance that is not easily explained by peripheral auditory profile or demographic factors. Thus, it is imperative to understand if auditory cognitive processes such as selective attention explain such variability. The presented study directly addressed this question by quantifying attentional modulation of cortical auditory responses during an attention task and comparing its individual differences with speech-in-noise performance. In our attention experiment, participants with CI were given a pre-stimulus visual cue that directed their attention to either of two speech streams and were asked to select a deviant syllable in the target stream. The two speech streams consisted of the female voice saying “Up” five times every 800 ms and the male voice saying “Down” four times every 1 s. The onset of each syllable elicited distinct event-related potentials (ERPs). At each syllable onset, the difference in the amplitudes of ERPs between the two attentional conditions (attended - ignored) was computed. This ERP amplitude difference served as a proxy for attentional modulation strength. Our group-level analysis showed that the amplitude of ERPs was greater when the syllable was attended than ignored, exhibiting that attention modulated cortical auditory responses. Moreover, the strength of attentional modulation showed a significant correlation with speech-in-noise performance. These results suggest that the attentional modulation of cortical auditory responses may provide a neural marker for predicting CI users’ success in clinical tests of speech-in-noise listening.

OBJECTIVES Despite the widespread use of noise reduction (NR) in modern digital hearing aids, our neurophysiological understanding of how NR affects speech-in-noise perception and why its effect is variable is limited. The current study aimed to (1) characterize the effect of NR on the neural processing of target speech and (2) seek neural determinants of individual differences in the NR effect on speech-in-noise performance, hypothesizing that an individual's own capability to inhibit background noise would inversely predict NR benefits in speech-in-noise perception. DESIGN Thirty-six adult listeners with normal hearing participated in the study. Behavioral and electroencephalographic responses were simultaneously obtained during a speech-in-noise task in which natural monosyllabic words were presented at three different signal-to-noise ratios, each with NR off and on. A within-subject analysis assessed the effect of NR on cortical evoked responses to target speech in the temporal-frontal speech and language brain regions, including supramarginal gyrus and inferior frontal gyrus in the left hemisphere. In addition, an across-subject analysis related an individual's tolerance to noise, measured as the amplitude ratio of auditory-cortical responses to target speech and background noise, to their speech-in-noise performance. RESULTS At the group level, in the poorest signal-to-noise ratio condition, NR significantly increased early supramarginal gyrus activity and decreased late inferior frontal gyrus activity, indicating a switch to more immediate lexical access and less effortful cognitive processing, although no improvement in behavioral performance was found. The across-subject analysis revealed that the cortical index of individual noise tolerance significantly correlated with NR-driven changes in speech-in-noise performance. CONCLUSIONS NR can facilitate speech-in-noise processing despite no improvement in behavioral performance. Findings from the current study also indicate that people with lower noise tolerance are more likely to get more benefits from NR. Overall, results suggest that future research should take a mechanistic approach to NR outcomes and individual noise tolerance.

We designed a spatial selective attention task to investigate a listener’s speech understanding ability in various masking noise conditions. The masking noise stream is music and non-intelligent speech combined sound which was played from the front-right and back directions. The target speech stream which has an auditory cue “Ready,” following color and number information, for example, ‘Ready Blue Five,’ was played from the front-left direction. A listener’s attentional ability was evaluated through the accuracy of the correct number and color selection in each condition of various SNRs and the spatial location of the masker. We formed two subject groups showing distinct cognitive styles, independent-analytic and interdependent-holistic, from a pre-experimental analysis. The analysis of variance (ANOVA) evinced a significant interaction between the group and SNR. Moreover, the independent-analytic group appeared to maintain their attention regardless of spatial location while another group scored poorly for the rear-positioned masker. Specifically, when the task got difficult with lower SNR conditions, this discrepancy between the two groups became significant. From these discussions, this study supports that individual differences associated with subconscious cognitive constructs influence speech-in-noise understanding ability.

ObjectivesCochlear implant (CI) users exhibit a large variance in understanding speech in noise (SiN). Past works in CI users found that spectral and temporal resolutions correlate with the SiN ability, but a large portion of variance has been remaining unexplained. Our group’s recent work on normal-hearing listeners showed that the ability of grouping temporally coherent tones in a complex auditory scene predicts SiN ability, highlighting a central mechanism of auditory scene analysis that contributes to SiN. The current study examined whether the auditory grouping ability contributes to SiN understanding in CI users as well.Design47 post-lingually deafened CI users performed multiple tasks including sentence-in-noise understanding, spectral ripple discrimination, temporal modulation detection, and stochastic figure-ground task in which listeners detect temporally coherent tone pips in the cloud of many tone pips that rise at random times at random frequencies. Accuracies from the latter three tasks were used as predictor variables while the sentence-in-noise performance was used as the dependent variable in a multiple linear regression analysis.ResultsNo co-linearity was found between any predictor variables. All the three predictors exhibited significant contribution in the multiple linear regression model, indicating that the ability to detect temporal coherence in a complex auditory scene explains a further amount of variance in CI users’ SiN performance that was not explained by spectral and temporal resolution.ConclusionsThis result indicates that the across-frequency comparison builds an important auditory cognitive mechanism in CI users’ SiN understanding. Clinically, this result proposes a novel paradigm to reveal a source of SiN difficulty in CI users and a potential rehabilitative strategy.

Introduction Older listeners have difficulty understanding speech in unfavorable listening conditions. To compensate for acoustic degradation, cognitive processing skills, such as working memory, need to be engaged. Despite prior findings on the association between working memory and speech recognition in various listening conditions, it is not yet clear whether the modality of stimuli presentation for working memory tasks should be auditory or visual. Given the modality-specific characteristics of working memory, we hypothesized that auditory working memory capacity could predict speech recognition performance in adverse listening conditions for older listeners and that the contribution of auditory working memory to speech recognition would depend on the task and listening condition. Methods Seventy-six older listeners and twenty younger listeners completed four kinds of auditory working memory tasks, including digit and speech span tasks, and sentence recognition tasks in four different listening conditions having multi-talker noise and time-compression. For older listeners, cognitive function was screened using the Mini-Mental Status Examination, and audibility was assured. Results Auditory working memory, as measured by listening span, significantly predicted speech recognition performance in adverse listening conditions for older listeners. A linear regression model showed speech recognition performance for older listeners could be explained by auditory working memory whilst controlling for the impact of age and hearing sensitivity. Discussion Measuring working memory in the auditory modality facilitated explaining the variance in speech recognition in adverse listening conditions for older listeners. The linguistic features and the complexity of the auditory stimuli may affect the association between working memory and speech recognition performance. Conclusion We demonstrated the contribution of auditory working memory to speech recognition in unfavorable listening conditions in older populations. Taking the modality-specific characteristics of working memory into account may be a key to better understand the difficulty in speech recognition in daily listening conditions for older listeners.

Background: Verbal communication comprises the retrieval of semantic and syntactic information elicited by various kinds of words (i.e., parts of speech) in a sentence. Content words, such as nouns and verbs, convey essential information about the overall meaning (semantics) of a sentence, whereas function words, such as prepositions and pronouns, carry less meaning and support the syntax of the sentence. Methods: This study aimed to identify neural correlates of the differential information retrieval processes for several parts of speech (i.e., content and function words, nouns and verbs, and objects and subjects) via electroencephalography performed during English spoken-sentence comprehension in thirteen participants with normal hearing. Recently, phoneme-related information has become a potential acoustic feature to investigate human speech processing. Therefore, in this study, we examined the importance of various parts of speech over sentence processing using information about the onset time of phonemes. Results: The distinction in the strength of cortical responses in language-related brain regions provides the neurological evidence that content words, nouns, and objects are dominant compared to function words, verbs, and subjects in spoken sentences, respectively. Conclusions: The findings of this study may provide insights into the different contributions of certain types of words over others to the overall process of sentence understanding.

Cochlear implants (CIs) have evolved to combine residual acoustic hearing with electric hearing. It has been expected that CI users with residual acoustic hearing experience better speech-in-noise perception than CI-only listeners because preserved acoustic cues aid unmasking speech from background noise. This study sought neural substrate of better speech unmasking in CI users with preserved acoustic hearing compared to those with lower degree of acoustic hearing. Cortical evoked responses to speech in multi-talker babble noise were compared between 29 Hybrid (i.e., electric acoustic stimulation or EAS) and 29 electric-only CI users. The amplitude ratio of evoked responses to speech and noise, or internal SNR, was significantly larger in the CI users with EAS. This result indicates that CI users with better residual acoustic hearing exhibit enhanced unmasking of speech from background noise.

Speech perception (especially in background noise) is a critical problem for hearing-impaired listeners and an important issue for cognitive hearing science. Despite a plethora of standardized measures, few single-word closed-set tests uniformly sample the most frequently used phonemes and use response choices that equally sample phonetic features like place and voicing. The Iowa Test of Consonant Perception (ITCP) attempts to solve this. It is a proportionally balanced phonemic word recognition task designed to assess perception of the initial consonant of monosyllabic consonant-vowel-consonant (CVC) words. The ITCP consists of 120 sampled CVC words. Words were recorded from four different talkers (two female) and uniformly sampled from all four quadrants of the vowel space to control for coarticulation. Response choices on each trial are balanced to equate difficulty and sample a single phonetic feature. This study evaluated the psychometric properties of ITCP by examining reliability (test-retest) and validity in a sample of online normal-hearing participants. Ninety-eight participants completed two sessions of the ITCP along with standardized tests of words and sentence in noise (CNC words and AzBio sentences). The ITCP showed good test-retest reliability and convergent validity with two popular tests presented in noise. All the materials to use the ITCP or to construct your own version of the ITCP are freely available [Geller, McMurray, Holmes, and Choi (2020). https://osf.io/hycdu/].

Listeners face the challenge of understanding speech every day. A key cognitive strategy for parsing speech in noisy environments relies on auditory selective attention, which recruits a network of multiple cortical regions. Our recent studies identified at least two different neural mechanisms of auditory attention. Space-based attention engages alpha oscillations in the parietal cortex, which are thought to cause lateral suppression of streams in the ignored portion in space. In contrast, talker identity-based attention modulates beta oscillations in the temporal lobe, suggesting that a neural pitch prediction mechanism in the middle temporal gyrus (MTG) focuses attention to talker. Based on these findings, here we use a brain perturbation method to establish causal links between such oscillatory activity and control of different forms of auditory attention. We hypothesize that perturbing alpha oscillations in parietal cortex will impair spatial attention while perturbing beta oscillations in the MTG will impair speaker identity-based attention. Our ongoing study utilizes repetitive transcranial magnetic stimulation (rTMS) to induce such perturbations in the pre-determined regions of interests non-invasively and safely. This presentation will provide proof-of-concept data to validate the feasibility of this approach.

Selective attention enhances cortical responses to attended sensory inputs while suppressing others, which can be an effective strategy for speech-in-noise (SiN) understanding. Emerging evidence exhibits a large variance in attentional control during SiN tasks, even among normal-hearing listeners. Yet whether training can enhance the efficacy of attentional control and, if so, whether the training effects can be transferred to performance on a SiN task has not been explicitly studied. Here, we introduce a neurofeedback training paradigm designed to reinforce the attentional modulation of auditory evoked responses. Young normal-hearing adults attended one of two competing speech streams consisting of five repeating words (“up”) in a straight rhythm spoken by a female speaker and four straight words (“down”) spoken by a male speaker. Our electroencephalography-based attention decoder classified every single trial using a template-matching method based on pre-defined patterns of cortical auditory responses elicited by either an “up” or “down” stream. The result of decoding was provided on the screen as online feedback. After four sessions of this neurofeedback training over 4 weeks, the subjects exhibited improved attentional modulation of evoked responses to the training stimuli as well as enhanced cortical responses to target speech and better performance during a post-training SiN task. Such training effects were not found in the Placebo Group that underwent similar attention training except that feedback was given only based on behavioral accuracy. These results indicate that the neurofeedback training may reinforce the strength of attentional modulation, which likely improves SiN understanding. Our finding suggests a potential rehabilitation strategy for SiN deficits.

Classification of spoken word-evoked potentials is useful for both neuroscientific and clinical applications including brain-computer interfaces (BCIs). By evaluating whether adopting a biology-based structure improves a classifier’s accuracy, we can investigate the importance of such structure in human brain circuitry, and advance BCI performance. In this study, we propose a semantic-hierarchical structure for classifying spoken word-evoked cortical responses. The proposed structure decodes the semantic grouping of the words first (e.g., a body part vs. a number) and then decodes which exact word was heard. The proposed classifier structure exhibited a consistent ∼10% improvement of classification accuracy when compared with a non-hierarchical structure. Our result provides a tool for investigating the neural representation of semantic hierarchy and the acoustic properties of spoken words in human brains. Our results suggest an improved algorithm for BCIs operated by decoding heard, and possibly imagined, words.

ObjectivesUnderstanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. Individuals vary in their ability to understand SiN. This cannot be explained by simple peripheral hearing profiles, but recent work by our group (Kim et al., 2021, Neuroimage) highlighted central neural factors underlying the variance in SiN ability in normal hearing (NH) subjects. The current study examined neural predictors of speech-in-noise ability in a large cohort of cochlear-implant (CI) users, with the long-term goal of developing a simple electrophysiological correlate that could be implemented in clinics.DesignWe recorded electroencephalography (EEG) in 114 post-lingually deafened CI users while they completed the California Consonant Test (CCT): a word-in-noise task. In many subjects, data were also collected on two other commonly used clinical measures of speech perception: a word-in-quiet task (Consonant-Nucleus-Consonant [CNC]) word and a sentence-in-noise task (AzBio sentences). Neural activity was assessed at a single vertex electrode (Cz), to maximize generalizability to clinical situations. The N1-P2 complex of event-related potentials (ERPs) at this location were included in multiple linear regression analyses, along with several other demographic and hearing factors as predictors of speech in noise performance.ResultsIn general, there was a good agreement between the scores on the three speech perception tasks. ERP amplitudes did not predict AzBio performance which was predicted by the duration of device use, low-frequency hearing thresholds, and age. However, ERP amplitudes were strong predictors for performance for both word recognition tasks: the CCT (which was conducted simultaneously with EEG recording), and the CNC (conducted offline). These correlations held even after accounting for known predictors of performance including residual low-frequency hearing thresholds. In CI-users, better performance was predicted by an increased cortical response to the target word, in contrast to previous reports in normal-hearing subjects in whom speech perception ability was accounted for by the ability to suppress noise.ConclusionsThese data indicate a neurophysiological correlate of speech-in-noise performance that can be relatively easily captured within the clinic, thereby revealing a richer profile of an individual’s hearing performance than shown by psychoacoustic measures alone. These results also highlight important differences between sentence and word recognition measures of performance and suggest that individual differences in these measures may be underwritten by different mechanisms. Finally, the contrast with prior reports of NH listeners in the same task suggests CI-users performance may be explained by a different weighting of neural processes than NH listeners.

Cochlear implants have evolved to utilize residual acoustic hearing that combines to electric stimulation, known as electric-acoustic stimulation (EAS). However, there are mixed expectations about the benefits of EAS. A positive perspective expects that contributions from residual hearing provide better access to acoustic cues that is helpful for speech-in-noise perception. An opposing view concerns potentially poorer spectral resolution of EAS electrodes’ stimulation as those electrodes are often inserted close to lateral wall, which may cause poorer speech-in-noise perception. This study aimed to directly compare neural processes of speech-in-noise perception between EAS and standard CI users to provide an answer to the above alternative expectations. We used 64-channel EEG to measure cortical evoked responses to (1) background noise and (2) target word while listeners perform a word-in-noise task. Then, we compared the amplitude ratio of evoked responses to the target word and background noise, referred to as “internal SNR,” which reflects how well target sound is unmasked from the mixture of speech and noise. Based on the comparison of 55 EAS and 22 standard CI users, internal SNR was significantly larger in EAS CI users. This result indicates that EAS provides enhanced neural processes for speech unmasking.

We designed a neurofeedback training paradigm to enhance the attentional modulation of cortical auditory evoked responses. Two concurrent speech streams—a female voice repeating “Up” five times and a male voice repeating “Down” four times in three secondsi—were played from left and right loudspeakers, respectively. Subjects were instructed to attend one of those streams by a pre-stimulus visual cue (e.g., “Target: Up”). Attention was decoded from single-trial EEG signals. Subjects received neurofeedback (i.e., a visual object on the computer screen moves upward if the EEG decoder determines the “up” stream was attended; or vice versa). Subjects repeated this training for four sessions across four weeks. During the last session, compared to the first, subjects exhibited strengthened alpha oscillation in the right parietal cortex while they attended right and ignored left, indicating that spatial inhibitory processing to suppress sounds left was enhanced. The temporal cortex exhibited greater attentional modulation of beta oscillation after the four weeks of training, indicating enhanced neural activity to predict the target. The strength of attentional modulation on cortical evoked responses to sounds was also improved. These results prove that neurofeedback training effectively enhances the cortical processing for auditory selective attention.

Speech perception, especially in background noise, is a critical problem for hearing impaired listeners, and an important issue for cognitive hearing science. Despite a plethora of standardized measures, there are few single-word, closed-set tasks that uniformly sample the phonetic space and which use response choices that balance all phonetic features. The Iowa Test of Consonant Perception (ITCP) was developed to solve this. It is a phonemically balanced word recognition task designed to assess perception of the initial consonant of monosyllabic consonant-vowel-consonant (CVC) words. The ITCP consists of 120 phonetically balanced CVC words. Words were recorded from four different talkers (two female), and uniformly sample from all four corners of the vowel space to control for coarticulation. Response choices on each trial are balanced to equate difficulty and sample a single phonetic feature. This study evaluated the psychometric properties of ITCP by examining reliability (test-retest) and validity in a sample of online normal hearing participants. Ninety-eight participants completed two sessions of the ITCP along with standardized tests of words and sentence in noise (CNC words and AzBio sentences). The ITCP showed good test-retest reliability and convergent validity with two popular speech-in-noise tasks. ITCP materials are freely available here: https://osf.io/hycdu/.

Background Pitch perception of complex tones relies on place or temporal fine structure-based mechanisms from resolved harmonics and the temporal envelope of unresolved harmonics. Combining this information is essential for speech-in-noise performance, as it allows segregation of a target speaker from background noise. In hybrid cochlear implant (H-CI) users, low frequency acoustic hearing should provide pitch from resolved harmonics while high frequency electric hearing should provide temporal envelope pitch from unresolved harmonics. How the acoustic and electric auditory inputs interact for H-CI users is largely unknown. Harmonicity and inharmonicity are emergent features of sound in which overtones are concordant or discordant with the fundamental frequency. We hypothesized that some H-CI users would be able to integrate acoustic and electric information for complex tone pitch perception, and that this ability would be correlated with speech-in-noise performance. In this study, we used perception of inharmonicity to demonstrate this integration. Methods Fifteen H-CI users with only acoustic hearing below 500 Hz, only electric hearing above 2 kHz, and more than 6 months CI experience, along with eighteen normal hearing (NH) controls, were presented with harmonic and inharmonic sounds. The stimulus was created with a low frequency component, corresponding with the H-CI user's acoustic hearing (fundamental frequency between 125 and 174 Hz), and a high frequency component, corresponding with electric hearing. Subjects were asked to identify the more inharmonic sound, which requires the perceptual integration of the low and high components. Speech-in-noise performance was tested in both groups using the California Consonant Test (CCT), and perception of Consonant-Nucleus-Consonant (CNC) words in quiet and AzBio sentences in noise were tested for the H-CI users. Results Eight of the H-CI subjects (53%), and all of the NH subjects, scored significantly above chance level for at least one subset of the inharmonicity detection task. Inharmonicity detection ability, but not age or pure tone average, predicted speech scores in a linear model. These results were significantly correlated with speech scores in both quiet and noise for H-CI users, but not with speech in noise performance for NH listeners. Musical experience predicted inharmonicity detection ability, but did not predict speech performance. Conclusions We demonstrate integration of acoustic and electric information in H-CI users for complex pitch sensation. The correlation with speech scores in H-CI users might be associated with the ability to segregate a target speaker from background noise using the speaker's fundamental frequency.

Auditory selective attention is a crucial mechanism for comprehending speech in noise. We investigated if cochlear implant (CI) users exhibit auditory selective attention that involves modulation of neural responses to target speech and if such attentional ability predicts their speech-in-noise performance. In our experiment, designed to assess the strength of attentional modulation, participants with normal hearing and with CI were given a pre-stimulus visual cue that directed their attention to either of two sequences in stationary background noise and asked to select a deviant syllable. We hypothesized that the amplitude of event-related-potential (ERP) would be greater when the syllable is attended if either group is capable of employing auditory selective attention and that the difference of ERP amplitude between attended and unattended trials predicts the performance in a speech-in-noise task. Our analysis showed that the amplitude of ERPs for the attended syllable was greater than that for the unattended syllable with the CI subjects, exhibiting that attention modulates CI users’ cortical responses to sounds. Moreover, the strength of attentional modulation showed a significant correlation with the same CI users’ speech-in-noise performance. These results show that attentional modulation provides a valuable neural marker for predicting CI users’ success in real-world communications.

Multichannel speech reinforcement exploiting DoA information is proposed.An empirical evidence of the binaural unmasking for monaural speech is provided.Proposed reinforcement restores perceived loudness considering binaural unmasking.The performance of the algorithm is verified through subjective listening tests. Speech reinforcement or near-end listening enhancement is a technique that modifies the far-end signal to mitigate the effect of the near-end noise, usually based on the power spectra of the far-end signal and the near-end noise. Psychoacoustic experiments have shown that the location of a noise source with respect to that of a signal source affects the amount of masking. Since conventional speech reinforcement methods obtain spectral gain based only on the power spectra, this psychoacoustic phenomenon called binaural unmasking has not been considered in those approaches. In this paper, we propose a novel speech reinforcement algorithm that modifies the far-end speech signal based on both the power spectrum and the direction-of-arrival (DoA) of the noise. Specifically, we have computed the equivalent frontal noise level from the observed noise level and the estimated DoA, and used it to compute spectral gains as in conventional partial loudness restoration-based speech reinforcement. Experimental results showed that the proposed method outperformed the conventional methods based on partial loudness restoration and speech intelligibility index (SII) optimization in terms of the overall perceived quality through subjective listening tests.

Both visual and auditory spatial selective attention result in lateralized alpha (8-14 Hz) oscillatory power in parietal cortex: alpha increases in the hemisphere ipsilateral to attentional focus. Brain stimulation studies suggest a causal relationship between parietal alpha and suppression of the representation of contralateral visual space. However, there is no evidence that parietal alpha controls auditory spatial attention. Here, we performed high definition transcranial alternating current stimulation (HD-tACS) on human subjects performing an auditory task in which they attended either spatial or nonspatial features. Alpha (10 Hz) but not theta (6 Hz) HD-tACS of right parietal cortex interfered with attending left but not right auditory space. Parietal stimulation had no effect for nonspatial auditory attention. Moreover, performance in post-stimulation trials returned rapidly to baseline. These results demonstrate a causal, frequency-, hemispheric-, and task-specific effect of parietal alpha brain stimulation on top-down control of auditory spatial attention.