Summary:
This review synthesizes evidence demonstrating that Phonak Roger remote microphone systems can significantly improve auditory processing and psychosocial outcomes across a wide range of populations, including individuals with hearing loss, neurodevelopmental disorders, and typical hearing.

Key Takeaways:

  1. Enhanced Auditory Function: Roger technology consistently improves speech perception in noise, reduces the impact of distance on hearing, and lowers listening effort across various settings and populations.
  2. Psychosocial Benefits: Use of Roger systems is associated with improved social interaction, reduced stress, and better behavioral outcomes, particularly among children with autism spectrum disorder.
  3. Research Gaps Identified: While current findings are promising, more longitudinal and neurophysiological research is needed to isolate Roger’s effects and determine long-term benefits.

This review consolidates existing literature on the effects of Phonak Roger remote microphone systems on auditory processing and psychosocial functions across diverse populations.

By Wanting Huang, PhD, and Jingjing Guan, PhD

1 Introduction

Auditory processing represents a fundamental aspect of human perception, serving as a basis for decoding and interpreting acoustic information from the environment. This capability facilitates essential functions such as language comprehension, musical appreciation, and environmental awareness.1, 2 The neurocognitive mechanisms involved in auditory processing, such as sound localization, temporal resolution, and binaural integration, are instrumental in extracting meaning from acoustic signals.3 However, the accuracy of auditory processing can be substantially impaired by noise,4, 5 reverberation, and distance,6,7 even among individuals with normal hearing.

Various auditory processing difficulties can adversely affect social interactions and emotional well-being.8 For example, children with auditory processing disorder (APD) may experience increased anxiety and social isolation due to the challenges of understanding speech in noisy environments and misinterpreting social cues.9 Similarly, older adults with hearing loss often face reduced socialization, which can subsequently lead to social isolation,10, 11loneliness,12 apathy,13 and depression.14-16 Therefore, identifying and addressing auditory processing difficulties in these populations is crucial for promoting positive psychosocial outcomes and preventing long-term challenges in social and emotional domains.

Phonak Roger is a wireless microphone system developed in 2013 to address challenges in auditory processing within adverse listening environments. It consists of a Roger transmitter and a compatible Roger receiver and is referred to as Roger technology throughout the remainder of this article. This advanced technology utilizes adaptive digital wireless transmission to enhance speech intelligibility amidst background noise and over distance. The Roger technology provides features beyond typical remote microphones, such as adaptive gain, low latency, multi-talker networks, and a wide portfolio of products for various use cases. Since its launch, it has gained large adoption primarily by individuals with hearing loss.17-19 However, studies have also indicated its potential benefits for those with neurodevelopmental disorders, such as autism spectrum disorder (ASD)20, 21 and listening difficulties.22 Research suggests that individuals with other neurodevelopmental conditions may experience auditory processing deficits even with normal audiometric thresholds.23, 24

The increasing adoption of Roger technology in this population necessitates a review of its impact on auditory processing and psychosocial functions, domains currently lacking comprehensive investigation in the existing literature. This review aims to synthesize disparate findings, clarifying the efficacy of Roger technology in these key areas. This work will provide hearing care professionals (HCPs) with evidence-based intervention strategies for different populations who could benefit from the technology’s use, while also identifying knowledge gaps to guide future research focused on optimizing the development and application of remote microphone technology for users.

2. Methods

The primary inclusion criteria for this review focused on studies assessing the impact of Roger technology on auditory processing and psychosocial functions in individuals of all ages, including those with typical hearing, hearing loss, and neurodevelopmental disorders. The comprehensive literature search was carried out on PubMed and the Phonak Evidence Library using a list of specific key words, guided by the PICO framework. This framework is recognized for aiding searchers in obtaining more relevant and precise results,25 as it structures the clinical question into four components: population (P), intervention (I), comparison (C), and outcome (O), 26 enhancing the specificity and conceptual clarity of the clinical problem. 

3. Results

From the search, we filtered out duplicates; articles not relevant to the topic of interest; studies that were not written in English; and types of publications such as systematic reviews, meta-analyses, and books. Ultimately, 21 peer-reviewed articles and 1 peer-reviewed scientific poster remained for the review. Across the 22 studies, participant demographics varied substantially, and very few of them reported effect sizes. Therefore, the data could not be pooled for meta-analyses, and the results are presented descriptively.

Roger Phonak remote microphone Figure 1
Figure 1. Comparisons of the speech reception thresholds with device and without device. *** indicates a significant difference between ‘with device’ condition and ‘without device’ condition.

3.1 Improved speech perception in noise

Seventeen of the 22 articles reviewed investigated the impact of Phonak Roger technology on speech perception in noisy environments. These studies consistently evaluated outcomes using two primary measures: speech recognition accuracy and speech reception thresholds (SRTs). Thirteen of these 17 articles specifically examined the effect of Roger technology on speech recognition accuracy. The   accuracy improvement was demonstrated both directly, through higher scores on standardized speech perception tests (e.g., Hearing in Noise Test, Consonant-Nucleus-Consonant [CNC] word test; Table 1) with Roger technology versus without,18-22, 27-31 and indirectly, through enhanced listening performance (e.g., following verbal instructions)32, 33 and improved academic outcomes.34 In line with these accuracy improvements, the research also showed that SRTs were significantly lower with Roger technology than without (Figure 1), indicating an improvement in speech reception thresholds ranging from 3 dB to 14.95 dB.17, 35-37

Table 1. Summary of study characteristics and results on the impact of Phonak Roger wireless microphones on the speech perception accuracy in noise, organized by publication year.

StudyParticipantsTest materialsSNR(s)Performance (M ± SD (%))
Without deviceWith device
Gaastra et al.(2024)2714 aneurysmal subarachnoid hemorrhage (aSAH) patients with self-reported hearing loss (i.e., auditory processing disorder, APD). The pure tone thresholds of all participants were <25 dB HL.All participants aged above 18 yrs old (mean age = 57.4 yrs).Bamford-Kowal-Bench (BKB) speech test-5 dB-10 dB25.00 ± 0.171.00 ± 0.0299.00 ± 0.02***97.00 ± 0.11***
Thibodeau et al. (2024)2810 normal-hearing adults aged between 20 and 63 years.The pure tone thresholds of all participants were within normal limits (≤ 20 dB HL) across frequency range of 250 to 4000 Hz.Hearing in Noise Test (HINT) 0 dB-5 dB-10 dBThe specific numbers are not listed. The results indicated that the mean HINT sentence recognition rates with Roger products (i.e., Roger Select and Roger Pen) were significantly higher compared to rates without these devices (ps < 0.001). Additionally, the mean HINT sentence recognition rate with the Roger Select was significantly higher than that with the Roger Pen (p < 0.001).
Zanin et al. (2024)3820 individuals (10 female, mean age = 72.9 yrs) with bilateral mild-to-moderate hearing loss. Participants were fitted with hearing aids binaurally at least two weeks prior to data collection.City University of New York-like sentences+8 dB+3 dB-2 dB-7 dB-12 dB-17 dB77.5 ± 25.367.1 ± 25.344.3 ± 26.022.5 ±20.97.8 ± 11.81.2 ± 1.493.3 ± 15.5 (n.s.)92.4 ± 19.2***89.1 ± 21.5***81.4 ± 21.5***58.0 ± 27.2***14.9 ± 15.6***
Shiels et al. (2023)22Children with listening difficulty (LiD) (N = 28, 17 males), mean age at assessment was 8y6m, range from 6y0m to 12y6m.AzBio sentence test+12 dB+5 dB0 dB-10 dB80.34 ± 11.7056.13 ± 17.5557.82 ± 14.6520.96 ± 11.7083.38 ± 11.88 (n.s.)77.53 ± 11.24**79.44 ± 12.88**70.91 ± 17.33**
Xu et al. (2023)20Children with autism spectrum disorder (ASD) group:26 children (3 female), age range: 6.8-12.1 yrs, IQ: 70-130.The Mandarin Hearing in Noise Test for Children (MHINT-C)0 dBThe specific numbers are not listed. The difference between two conditions was significant, with p value being smaller than .001.
Rance et al. (2022)2910 school-age children (7-17 yrs old) with neurofibromatosis type 1 were randomly assigned to one of two treatment sequences: (1) active device for 2 weeks followed by inactive device for 2 weeks; (2) inactive device for 2 weeks followed by active device for 2 weeks.5 out of 10 children had a diagnosis of ADHD.Consonant-Nucleus-Consonant (CNC) word test0 dB41.4 ± 10.257.8 ± 8.3***
Keller (2021)3214 children with minimally verbal autismAll had normal hearing status.Aged from 4y 10m to 16y 8m.Listening performance was represented by three categories: social press, objective press and direction following press. Each category had three difficulty levels. Prompt level and response latency were used as outcome measures.Speech level was not mentioned. The background noise was at 55 dB SPL.Both the prompt level and response latency were significantly improved during the remote microphone (RM)-on condition (ps < 0.05). Further analysis indicated that such improvements were only seen for the non-social presses (i.e., objective press and direction following press) rather than the social press.
Keller et al. (2021)338 children with autism spectrum disorder (ASD) and language disorder. All had normal hearing status.Aged from 46 to 57 months.Listening performance was assessed using three instructional presses: response to name, object identification, and completion of a one-step direction. Prompt level and response latency were used as outcome measures.+14 dB or above.Compared to the remote microphone (RM)-off condition, all participants were able to complete tasks in the RM-on condition. Five out of eight participants showed significant improvements in their functional listening performance in the RM-on condition.
Shannan (2020)34495 primary three learners (mean age=7.05 years). 278 were in the intervention group (with remote microphone (RM)) and 217 were in the control group.These children were recruited from the most deprived (Scottish Index of Multiple Deprivation – SIMD Quintile 1) and least deprived (SIMD Quintile 5) areas.All children had normal hearing.Achievement for Excellence (AfE – InCAS) assessments. Modules included: a) developed ability (picture vocabulary, non-verbal ability), b) general mathematics (Number 1& 2, Data handling, Measure/shape/Space), c) mental arithmetic, d) reading and spelling (word recognition, word decoding, reading comprehension, spelling).Symbol-supported questionnaires for learners and standard questionnaires for teachers regarding noise perception, sources, feelings about noise, and ease of hearing the teacher.Not mentioned.Learners exposed to dynamic soundfield showed significantly greater improvements from pre-test to post-test compared to the control group on:a) Developed Ability (Picture Vocabulary, Non-Verbal Ability, overall module);b) Reading Module (Word Recognition, Word Decoding, Reading Comprehension, overall module);c) Mental Arithmetic Module.Dynamic soundfield significantly reduced the attainment gap between SIMD 1 (intervention) and SIMD 5 (control) learners in Non-Verbal Ability and Word Recognition.SIMD 1 learners (most deprived) in intervention classrooms showed significant gains, particularly in Developed Ability and Word Decoding.SIMD 5 learners (least deprived) in intervention classrooms showed significant gains, particularly in Data Handling and Measure/Shape/Space.Learners in intervention classrooms reported hearing the teacher significantly more easily across various teaching scenarios compared to controls (confirmed by logistic regression). Teachers generally reported positive effects of the soundfield on learners hearing/responding.
Thibodeau (2020)18Ten listeners (aged 20-92 yrs) with bilateral sensorineural hearing loss.All were experienced HA/CI users.Five of them had more than five years’ experience with remote microphone systems.Hearing in Noise Test (HINT)+5 dB0 dB-5 dB-10 dBThe specific numbers are not listed. Across noise levels, the performance in the Roger Select condition (with device; 88.21% ± 1.83) and Roger pen condition (with device; 76.31% ± 2.61) was significantly better than the hearing aid/cochlear implant-only condition (without device; 46.14% ± 3.53)***.
Rance et al. (2017)2116 children with ASD (mean age = 9.5 yrs, ranged from 6.0 to 12.0 yrs).Children were asked to use devices at home and at school for 4-6 hours/day for 1-2 weeks (mean: 8.8 days). Consonant-Nucleus-Consonant (CNC) word test0 dB59.9 ± 16.988.0 ± 13.3***
Wolfe et al. (2015)3017 adults (age range: 18-89 yrs) with more than 6-month use of hearing aids.AzBio sentence test+10 dB0 dB-10 dB-15 dBThe specific numbers are not listed. Throughout all noise levels, accuracies with device were significantly higher than those without device (p < .005).
Wolfe et al. (2013)31Seven adults implanted with OPUS 2 sound processor with MED-EL SONATA TI100.Hearing in Noise Test (HINT)0 dB-5 dB-10 dB-15 dBThe specific numbers are not listed. Accuracies with the Roger wireless microphone (with device) were significantly higher than those with other dynamic frequency modulation systems (without device) in adverse listening SNRs (-10 and -15 dB) *.
Note that * is used to indicate the significance level of difference between ‘with device’ condition and ‘without device’ condition. *: p < 0.05; **: p < 0.01; ***: p < 0.001; n.s.: not significant.SNR: signal-to-noise ratio; M: mean; SD: standard deviation.

3.2 Reduced impact of distance on speech perception

Selected studies also indicate that Roger technology mitigated the detrimental effects of distance on speech communication for target uses. For example, research comparing children’s speech access at home during typical weekends, with and without Roger technology, revealed notable findings. Although caregivers produced a comparable quantity of speech overall across both weekend conditions, children with hearing loss demonstrated significantly greater access to speech when using Roger technology.39, 40 Specifically, these children experienced approximately 42% more words39 and a 12% increase in child-directed speech per day.40 Concurrently, the implementation of Roger technology resulted in a significant reduction in caregivers’ speech modifications.41

Compared to conditions without Roger technology, caregivers demonstrated a decrease in casual repetitions (1.75 ± 0.34 (with Roger) vs. 2.79 ± 0.50 (without Roger)), intentional repetitions (2.49 ± 1.22 (with Roger) vs. 8.74 ± 5.33 (without Roger)), and alerting phrases (1.44 ± 0.39 (with Roger) vs. 3.46 ± 0.65 (without Roger)). 41

Table 2. Summary of scores on listening effort before and after using the Roger technology.

StudyParticipantsMeasurements Outcomes (pre- vs. post-use)
Gaastra et al. (2024)2714 aneurysmal subarachnoid hemorrhage (aSAH) patients with self-reported hearing loss (i.e., auditory processing disorder, APD). The pure tone thresholds of all participants were <25 dB HL.All participants aged above 18 yrs old (mean age = 57.4 yrs).Scores of the use of Roger wireless microphones: “Did the listening device make listening less of an effort?”The mean response to the question was 85 out of 100 (SD ± 24).
Xu et al. (2023)20Children with autism spectrum disorder (ASD) group: 26 children (3 female), age range: 6.8-12.1 yrs, IQ: 70-130.Scores of Children’s Auditory Performance Scale (CHAPS).There was a significantly decrease in listening difficulty ratings across all conditions (i.e., quiet, noise, ideal, multiple inputs) after device use (ps < .001).
Rance et al. (2022)2910 school-age children (7-17 yrs old) with neurofibromatosis type 1 were randomly assigned to one of two treatment sequences: (1) active device for 2 weeks followed by inactive device for 2 weeks; (2) inactive device for 2 weeks followed by active device for 2 weeks.5 out of 10 children had a diagnosis of ADHD.Scores of the Listening Inventory for Education-Revised (LIFE-R).The mean LIFE-R scores of the post-use condition (78% ± 22.5%) was significantly higher than those of the pre-use condition (54.6% ± 28.8%)(p <0.05).
Wagener et al. (2018)4315 (four female) older adults (aged from 63 to 83 yrs) with severe hearing impairment. All of them had more than 9 years of HA use, and none of them had previous experience with remote microphone (RM).Behavioral performance in the dual-task paradigm (primary task: the Oldenburg sentence test; secondary task: the Gottingen sentence test).Speech intelligibility in the post-use condition was significantly higher than that in the pre-use condition (p<0.001), indicating less listening effort upon using Roger wireless microphones.
Rance et al. (2017)2116 children with ASD (mean age = 9.5 yrs, ranged from 6.0 to 12.0 yrs).Children were asked to use devices at home and at school for 4-6 hours/day for 1-2 weeks (mean: 8.8 days)Scores of the Abbreviated Profile of Hearing Aid Benefit (APHAB).The Score of the Background Noise subscale was significantly lower in the post-use condition (28.7% ± 11.3%) compared to the pre-use condition (51.6% ± 20.0%) (p <0.001).
Schafer et al. (2016)3612 children (age range: 6-17 yrs) who were diagnosed with ASD as their primary disability. All had normal hearing.Verbal abilities varied substantially across participants.Scores of teacher LIFE-R, student LIFE-R, Children’s Home Inventory for Listening Difficulties (CHILD).Teacher LIFE-R: significantly reduced listening difficulty was rated in the post-use condition compared to the pre-use condition (p <0.05);Student LIFE-R: significantly reduced listening difficulty was rated in the post-use condition compared to the pre-use condition (p <0.05);CHILD: significant benefits of using Roger wireless microphones were seen in all conditions (i.e., quiet, noise, at a distance, in social situations) (ps < .05).
Joshi et al. (2014)37A 73-year-old retired male; had normal-to-profound sloping sensorineural hearing loss in the left ear and normal-to-moderately severe sloping sensorineural hearing loss in the right ear; had no previous experience with hearing aids.Scores on the Client Oriented Scale of Improvement (COSI).The participant’s subjective evaluation on the use of the Roger wireless microphone was positive.

SD: standard deviation.

3.3 Reduced listening effort

Reduced listening effort represents another key benefit associated with Roger technology. Listening effort, defined as the deliberate allocation of cognitive resources required to overcome perceptual obstacles in pursuit of a specific auditory goal, is particularly salient when tasks demand focused listening.42 Elevated levels of listening effort are commonly experienced by individuals with hearing loss, and in any situation where the auditory signal quality is compromised. 

Among the 22 selected articles, a subset of seven studies rigorously investigated and compared listening effort levels both prior to and following the implementation of Roger technology. These investigations encompassed a variety of auditory tasks administered across diverse scenarios, including ecologically valid classroom settings, controlled laboratory environments, and naturalistic home environments. 

As detailed in Table 2, these studies employed a range of methodologies to assess listening effort. These methods included simple oral questioning techniques,27 validated questionnaires such as the Children’s Auditory Performance Scale (CHAPS)20 and the Listening Inventory for Education-Revised (LIFE-R), 29 as well as objective behavioral measurements.43 Across these diverse methodological approaches, the findings consistently indicate a statistically significant reduction in listening effort for users of Roger technology. This robust body of evidence suggests that Roger technology effectively minimizes the cognitive resources necessary for individuals to successfully engage in and complete auditory tasks.

3.4 Enhanced psychosocial functions

In addition to improved auditory processing—such as better speech perception in noise, reduced listening effort, and more access to speech at a distance—psychosocial functions have also been shown to be enhanced among users of Roger technology. Initial evidence came from parent questionnaires (CHILD) and student self-reports (LIFE-R), which indicated significant benefits in social situations after using Roger wireless microphones.36 Further research explored potential underlying mechanisms.

Given that stress is negatively correlated with psychosocial functions in individuals with autism spectrum disorder,44, 45Rance et al investigated the impact of Roger technology on stress levels among a group of children with ASD. By comparing salivary cortisol concentrations before and after device use, researchers found a significant reduction with Roger technology (-0.18 nmol/L ± 0.45 nmol/L) compared to the pre-use condition (0.30 nmol/L ± 0.56 nmol/L). This demonstrated decreased stress levels, indirectly suggesting a positive pathway to improved psychosocial function.21

Building on this foundation and providing more direct evidence for psychosocial function, Leung et al.46 combined a remote microphone hearing system (RMHS; i.e., Roger technology) with targeted computerized emotion perception training for children with ASD. After one year of intervention, these children showed significant improvements in behavioral social scores, ultimately exceeding those of their typically developing peers. Notably, these behavioral gains were supported by electrophysiological (EEG) evidence. Post-intervention recordings showed altered cortical auditory evoked potentials (CAEPs), including shorter mismatch negativity (MMN) latencies and enhanced neural differentiation of emotional stimuli, indicating improved underlying auditory processing that aligned with the observed behavioral gains.46

This convergence of behavioral and neurophysiological data strongly supports the positive impact of interventions incorporating Roger technology on psychosocial functions in children with ASD.

4 Discussion

Since its inception in 2013, Phonak Roger technology has been the subject of a growing body of research investigating its efficacy across diverse clinical populations. This review synthesized findings from 22 studies, revealing a consistent pattern of benefits associated with the use of Roger technology. The aggregated evidence demonstrates that Roger technology is effective in enhancing crucial aspects of auditory processing and psychosocial function. 

Specifically, statistically significant improvements were consistently reported in speech recognition in noise,17-22, 27-37a mitigation of the detrimental effects of distance on speech perception,39-41 and a reduction in listening effort.20, 21, 27, 29, 36, 37, 43 These benefits were observed across a wide range of users, including normal-hearing adults,28 children and adults with hearing loss using hearing aids or cochlear implants,17-19, 30, 31, 35, 39-41, 43 individuals with normal hearing thresholds but presenting with listening difficulties22 or auditory processing disorder,27 and individuals with neurodevelopmental disorders such as autism spectrum disorder20, 21, 32-34, 36, 46 and neurofibromatosis Type 1.29

The observed improvements in fundamental auditory processing skills are likely to contribute to broader functional benefits. Enhanced speech perception in challenging environments and reduced listening effort may facilitate better academic engagement,34 increased participation in social interactions,36 and reduced listening-related stress.21 The diversity of populations studied underscores the robustness of Roger technology in addressing listening challenges arising from various etiologies, including both peripheral hearing loss and central auditory processing difficulties.

A key insight from this review is that the evidence supporting Roger technology’s efficacy has relied predominantly on behavioral measures. While behavioral outcomes (e.g., speech perception scores, questionnaire ratings) offer strong face validity regarding end-user benefit and are often simpler to obtain in clinical or educational settings, they provide limited insights into the underlying neural mechanisms mediating these improvements. Furthermore, subjective reports may be confounded by factors such as listener motivation, attention, and placebo effects.

Luckily, recent research has begun to bridge this gap by exploring the electrophysiological correlates of interventions involving Roger technology. Notably, Leung et al46 combined Roger technology with targeted computerized emotion perception training for children with ASD. To our knowledge, this study is the first to provide neurophysiological evidence supporting the behavioral outcomes. We found that the improved social perception scores were associated with post-intervention EEG changes, including altered CAEPs indicating enhanced neural processing of emotional stimuli, and faster MMN responses. 

However, it is crucial to interpret these neurophysiological findings with caution. The observed changes resulted from the combined effects of Roger technology and the specific auditory-cognitive training program used. The current evidence does not allow for the definitive isolation of the electrophysiological impact attributable solely to the use of Roger technology itself. Disentangling these effects necessitates future research specifically designed to evaluate the neural consequences of Roger technology use independent of concurrent structured training paradigms.

Despite consistent positive findings, several limitations within the current evidence base warrant consideration. Many studies included in this review featured relatively small sample sizes, potentially limiting statistical power and the generalizability of results. Furthermore, participant heterogeneity across studies, particularly concerning comorbidities (e.g., Schafer et al36 included children with ASD, many of whom also had ADHD), makes it challenging to conclusively attribute observed benefits to Roger technology in individuals with a ‘pure’ primary diagnosis. This variability underscores the need for careful participant characterization and recruitment in future work. Additionally, most studies have focused on immediate or short-term outcomes (often within weeks of device fitting), leaving the long-term effects and sustainability of benefits largely unknown.

Future Research

Building on the existing evidence and its limitations, we identified multiple potential directions for future research. There is a clear need for longitudinal studies to track the effects of Roger technology over extended periods, assessing the persistence of benefits and potential developmental impacts. Larger-scale investigations with well-defined, homogeneous participant groups are required to strengthen the evidence base for specific populations and potentially identify predictors of successful outcomes. 

Crucially, research employing objective neurophysiological and neuroimaging techniques (e.g., EEG/ERP, fNIRS) is essential to elucidate the specific neural mechanisms through which Roger technology impacts auditory processing and reduces listening effort, ideally using paradigms that control for or isolate the effects of the technology from other interventions. 

Exploring the utility of Roger technology in broader populations—such as children who pass standard hearing screenings but exhibit auditory processing difficulties associated with ADHD, dyslexia, or other learning disorders—represents another important direction. 

Finally, comparative effectiveness studies evaluating different remote microphone systems could provide valuable clinical guidance.

5 Conclusion

This review provides a comprehensive understanding of the significant positive impact of Roger technology on auditory processing and social functioning across diverse populations. While the assumption is that most remote microphones will function similarly, the research in this review provides evidence of the benefits of Roger technology, in particular. Based on the data presented, hearing care professionals can expect this remote microphone solution to provide benefits to patients in various populations. Continued research and advancement in wireless microphone technology will likely yield an even higher quality of life for individuals with listening challenges in the future.

About the Authors:

Author Wanting Huang, PhD Wanting Huang has been conducting research on speech and auditory processing from a cognitive neuroscience perspective. She earned her PhD in Speech and Hearing Sciences from the University of Hong Kong in 2021. From 2021 to 2023, she engaged in postdoctoral research at the Southern University of Science and Technology. Since 2024, she has been working as a senior hearing researcher at Sonova Innovation Center in Shanghai. Email: [email protected]

Author Jingjing Guan, PhD Jingjing Guan holds a PhD from University of Texas at Austin and worked in Texas Tech University Health Sciences Center as an assistant professor and a licensed audiologist. She started her journey with Sonova Innovation Center in Shanghai in 2018. Her main research interests include psychoacoustics and hearing aid outcome measures. Email: [email protected]

References

1.          Richard, G.J., Language processing versus auditory processing. Auditory processing disorders: Assessment, management, and treatment, 2013: p. 283-299.

2.          Kyrtsoudi, M., et al. Auditory processing in musicians, a cross-sectional study, as a basis for auditory training optimization. in Healthcare. 2023. MDPI.

3.          Yang, J. and P. Li, Mechanisms for auditory perception: A neurocognitive study of second language learning of Mandarin Chinese.Brain Sciences, 2019. 9(6): p. 139.

4.          Gordon-Hickey, S., R.E. Moore, and J.M. Estis, The impact of listening condition on background noise acceptance for young adults with normal hearing. Journal of Speech, Language, and Hearing Research, 2012. 55(5): p. 1356-1372.

5.          Kumar, U.A., S. Ameenudin, and A. Sangamanatha, Temporal and speech processing skills in normal hearing individuals exposed to occupational noise. Noise and Health, 2012. 14(58): p. 100-105.

6.          Kolarik, A.J., et al., Auditory distance perception in humans: a review of cues, development, neuronal bases, and effects of sensory loss.Attention, Perception, & Psychophysics, 2016. 78: p. 373-395.

7.          Westermann, A. and J.M. Buchholz, The effect of spatial separation in distance on the intelligibility of speech in rooms. The Journal of the Acoustical Society of America, 2015. 137(2): p. 757-767.

8.          Bellis, T.J., When the brain can’t hear: Unraveling the mystery of auditory processing disorder. 2002: Simon and Schuster.

9.          Kreisman, N.V., et al., Psychosocial status of children with auditory processing disorder. Journal of the American Academy of Audiology, 2012. 23(03): p. 222-233.

10.        Dawes, P., et al., Hearing loss and cognition: the role of hearing AIDS, social isolation and depression. PloS one, 2015. 10(3): p. e0119616.

11.        Mick, P., I. Kawachi, and F.R. Lin, The association between hearing loss and social isolation in older adults. Otolaryngology–Head and Neck Surgery, 2014. 150(3): p. 378-384.

12.        Palmer, A.D., J.T. Newsom, and K.S. Rook, How does difficulty communicating affect the social relationships of older adults? An exploration using data from a national survey. Journal of communication disorders, 2016. 62: p. 131-146.

13.        Sugawara, N., et al., Hearing impairment and cognitive function among a community-dwelling population in Japan. Annals of general psychiatry, 2011. 10: p. 1-6.

14.        Rutherford, B.R., et al., Sensation and psychiatry: linking age-related hearing loss to late-life depression and cognitive decline.American Journal of Psychiatry, 2018. 175(3): p. 215-224.

15.        Kiely, K.M., K.J. Anstey, and M.A. Luszcz, Dual sensory loss and depressive symptoms: the importance of hearing, daily functioning, and activity engagement. Frontiers in human neuroscience, 2013. 7: p. 837.

16.        Amieva, H., et al., Death, depression, disability, and dementia associated with self-reported hearing problems: a 25-year study. The Journals of Gerontology: Series A, 2018. 73(10): p. 1383-1389.

17.        Griffin, A.M., et al., Effect of hearing device use on speech-in-noise performance in children with severe-to-profound unilateral hearing loss. Ear and Hearing, 2023. 44(3): p. 588-602.

18.        Thibodeau, L.M., Benefits in speech recognition in noise with remote wireless microphones in group settings. Journal of the American Academy of Audiology, 2020. 31(06): p. 404-411.

19.        Zanin, J., et al., Evaluating benefits of remote microphone technology for adults with hearing loss using behavioural and predictive metrics. International Journal of Audiology, 2024: p. 1-9.

20.        Xu, S., et al., Hearing assistive technology facilitates sentence-in-noise recognition in Chinese children with autism spectrum disorder.Journal of Speech, Language, and Hearing Research, 2023. 66(8): p. 2967-2987.

21.        Rance, G., et al., Reducing listening-related stress in school-aged children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 2017. 47: p. 2010-2022.

22.        Shiels, L., D. Tomlin, and G. Rance, The Assistive Benefits of Remote Microphone Technology for Normal Hearing Children With Listening Difficulties. Ear and Hearing, 2023. 44(5): p. 1049-1060.

23.        Haesen, B., B. Boets, and J. Wagemans, A review of behavioural and electrophysiological studies on auditory processing and speech perception in autism spectrum disorders. Research in autism spectrum disorders, 2011. 5(2): p. 701-714.

24.        O’Connor, K., Auditory processing in autism spectrum disorder: a review. Neuroscience & Biobehavioral Reviews, 2012. 36(2): p. 836-854.

25.        Agoritsas, T., et al., Sensitivity and predictive value of 15 PubMed search strategies to answer clinical questions rated against full systematic reviews. Journal of medical Internet research, 2012. 14(3): p. e2021.

26.        Huang, X., J. Lin, and D. Demner-Fushman. Evaluation of PICO as a knowledge representation for clinical questions. in AMIA annual symposium proceedings. 2006.

27.        Gaastra, B., et al., An assistive listening device improves hearing following aneurysmal subarachnoid haemorrhage. European Journal of Neurology, 2024. 31(5): p. e16240.

28.        Thibodeau, L.M., et al., Benefits of speech recognition in noise using remote microphones for people with typical hearing. Journal of Communication Disorders, 2024. 112: p. 106467.

29.        Rance, G., et al., A randomized controlled trial of remote microphone listening devices to treat auditory deficits in children with neurofibromatosis type 1. Neurological Sciences, 2022. 43(9): p. 5637-5641.

30.        Wolfe, J., et al., Evaluation of performance with an adaptive digital remote microphone system and a digital remote microphone audio-streaming accessory system. American Journal of Audiology, 2015. 24(3): p. 440-450.

31.        Wolfe, J., et al., Better speech recognition with digital RF system in study of cochlear implants. The Hearing Journal, 2013. 66(7): p. 24-26.

32.        Keller, M.A., Listening Difficulty in Children with Autism Spectrum Disorder: Evaluation and Intervention. 2021, Vanderbilt University.

33.        Keller, M.A., A.M. Tharpe, and J. Bodfish, Remote microphone system use in preschool children with autism spectrum disorder and language disorder in the classroom: A pilot efficacy study. 2021, American Speech-Language-Hearing Association.

34.        Shannan, B.B., Impact of dynamic soundfield on delivering improvements in educational attainment and closing the attainment gap with young learners in mainstream primary school. 2020.

35.        De Ceulaer, G., et al., Speech understanding in noise with the Roger Pen, Naida CI Q70 processor, and integrated Roger 17 receiver in a multi-talker network. European Archives of Oto-rhino-laryngology, 2016. 273: p. 1107-1114.

36.        Schafer, E.C., et al., Assistive technology evaluations: Remote-microphone technology for children with autism spectrum disorder.Journal of communication disorders, 2016. 64: p. 1-17.

37.        Joshi, A., Wright, S., Thibodeau, L., & Schaper, L., Demonstrating benefits of assistive technology to an adult with hearing loss. Poster presented at: Spring Intensive Auditory Rehabilitation Conference, 2014.

38.        Zanin, J., et al., Evaluating benefits of remote microphone technology for adults with hearing loss using behavioural and predictive metrics. International Journal of Audiology, 2025. 64(4): p. 327-335.

39.        Benítez-Barrera, C.R., G.P. Angley, and A.M. Tharpe, Remote microphone system use at home: Impact on caregiver talk. Journal of Speech, Language, and Hearing Research, 2018. 61(2): p. 399-409.

40.        Benítez-Barrera, C.R., et al., Remote microphone system use at home: impact on child-directed speech. Journal of Speech, Language, and Hearing Research, 2019. 62(6): p. 2002-2008.

41.        Thompson, E.C., et al., Remote microphone system use in the homes of children with hearing loss: Impact on caregiver communication and child vocalizations. Journal of Speech, Language, and Hearing Research, 2020. 63(2): p. 633-642.

42.        Pichora-Fuller, M.K., et al., Hearing impairment and cognitive energy: The framework for understanding effortful listening (FUEL).Ear and hearing, 2016. 37: p. 5S-27S.

43.        Wagener, K.C., et al., Effect of hearing aid directionality and remote microphone on speech intelligibility in complex listening situations. Trends in hearing, 2018. 22: p. 2331216518804945.

44.        Bishop‐Fitzpatrick, L., et al., The relationship between stress and social functioning in adults with autism spectrum disorder and without intellectual disability. Autism Research, 2015. 8(2): p. 164-173.

45.        Putnam, S.K., et al., Salivary cortisol levels and diurnal patterns in children with autism spectrum disorder. Journal of Developmental and Physical Disabilities, 2015. 27: p. 453-465.

46.        Leung, J.H., S.C. Purdy, and P.M. Corballis, Improving emotion perception in children with autism spectrum disorder with computer-based training and hearing amplification. Brain Sciences, 2021. 11(4): p. 469.