Despite the success of speech separation approaches for dry (non-reverb) speech mixtures, speech separation in naturalistic, spatial, and reverberant acoustic environments remains challenging. This limits the effectiveness of current speech separation methods for assistive hearing devices as well as neuroprosthetic devices such as cochlear implants (CIs). Here, we investigate whether a deep neural network model for speech separation can utilize the spatial information in naturalistic listening scenes as captured by a CI’s microphones to improve separation performance. We examined the impact of latent spatial cues (inherently present in two-channel speech mixtures, but need to be learned from these mixtures), as well as pre-computed spatial cues added to the speech mixtures as auxiliary input features (inter-channel level and phase differences, ILDs and IPDs). Specifically, we introduce a two-channel version of the SuDoRM-RF speech separation model, which takes as input speech mixtures recorded with two CI microphones and shows that latent spatial cues enhance separation performance without affecting model efficiency in terms of model complexity and inference latency. Pre-computed spatial cues – especially IPDs – enhanced separation performance even more, but simultaneously reduced model efficiency. Finally, simulating a CI user’s listening experience with a vocoder showed that the beneficial effect of spatial cues on DNN speech separation persists even if the separated speech streams are spectrotemporally degraded as in the output of a CI.

OBJECTIVES: The pupil dilation response is often used as a physiological measure of listening effort. One way to manipulate listening effort is to manipulate intelligibility. Only a few studies assessed the relationship between intelligibility and the pupil dilation response in cochlear implant (CI) users. Those studies did not consistently replicate the effects of intelligibility on the pupil dilation response evoked by sentence recognition in noise as observed in individuals with typical hearing or hard of hearing. Therefore, this study examined the effects of intelligibility on the pupil dilation response in CI users using several types of speech material. The type of masker is also known to influence listening effort as measured by pupillometry in individuals with typical hearing and hard of hearing. To our knowledge, this is not yet investigated in CI users. Therefore, this was also assessed in the current study. Finally, to account for subjective experiences, ratings of listening effort, difficulty, performance, and tendency of giving up were assessed. DESIGN: Twenty-eight postlingually deafened adult unilateral or bimodal CI users participated. Their ages ranged from 41 to 71 yrs old (mean = 58.4). A 3 × 3 within-subjects design was used with 3 intelligibility conditions (quiet, 50%, and 20% intelligibility in continuous noise) and 3 types of speech material (digit triplets, consonant-vowel-consonant [CVC] words, everyday sentences). Linear mixed model analyses assessed the effects of speech material and intelligibility condition on the mean pupil dilation (MPD), peak pupil dilation (PPD), and baseline pupil size (BPS). A paired sample t test was used to compare the effect of masker type (continuous noise versus a single interfering speaker) on these pupil measures for 50% sentence intelligibility. For all conditions, participants rated their experienced listening effort, difficulty, performance, and tendency of giving up. RESULTS: In the main analysis (N = 23), MPD, PPD, and BPS differed between the speech materials, but these measures did not depend on speech intelligibility. CVC words elicited the lowest MPDs and PPDs, followed by digit triplets and everyday sentences, with the latter showing the most pronounced pupil responses. The BPS was larger for sentences compared with CVC words and digit triplets. CVC words and sentences were rated as the most effortful and difficult, with the lowest self-perceived performance, and evoking the highest tendency to give up. Self-perceived performance was furthermore influenced by intelligibility (quiet > 50% > 20%). The other subjective ratings, such as listening effort, decreased with increasing intelligibility. A separate analysis on the data for the digit triplet material, including all CI users (n = 28), showed an intelligibility effect on the PPD. Finally, the analysis (N = 15) of the effect of masker type showed that PPDs and BPSs were larger for sentences masked with an interfering speaker compared with continuous noise. CONCLUSIONS: The intelligibility conditions in this study did not result in any measurable differences in listening effort, as indicated by the pupil dilation responses of unilateral or bimodal postlingually deafened CI users for everyday sentences or CVC words. A main effect of intelligibility condition on PPD was only found for digit triplets. Speculatively, this may be because the relative simplicity and low cognitive load evoked by this speech material allowed intelligibility effects to become apparent in this specific group of listeners. Subjective ratings indicated greater listening effort, difficulty, and a tendency to give up at lower intelligibility levels. When sentences were masked with an interfering speaker, both PPD and subjective listening effort increased compared with masking with continuous noise. These findings suggest that manipulating masker type can alter the pupil dilation response and perceived listening effort in CI users, even when using everyday sentences.

Introduction: Cochlear implantation (CI) is the standard treatment for severe-to-profound sensorineural hearing loss, but CI users often struggle with speech understanding in noisy environments. The Dutch/Flemish Matrix test is frequently used to evaluate speech-in-noise performance due to its assumed immunity to learning effects. However, studies challenge this assumption, revealing significant learning effects that can confound research outcomes. In this study, we modeled the learning curves of the Dutch/Flemish Matrix test to assess the influence of both between-session and between-test effects. We hypothesized that a exponential model would describe the learning effects more accurately than a linear model. Methods: The perceptual learning effects associated with the Dutch/Flemish Matrix test were assessed in 17 bimodal CI users. All participants performed the Matrix speech-in-noise tests across four sessions, with 13 randomized tests per session. The tests were conducted in a soundproof booth with an eight-speaker babble noise. The outcome parameter was the speech recognition threshold and was analyzed with a linear mixed model to account for confounders. Results: The results showed a statistically significant learning effect between sessions that added up to a speech intelligibility increase of 1.3 dB signal-to-noise ratio (SNR) (equivalent to ∼10% word score) between the first and second sessions, 0.86 dB SNR (∼7%) between the second and third sessions and 0.67 dB SNR (∼5%) between the third and fourth sessions. In addition, a statistically significant within-session learning effect (i.e., between tests) was observed with a linear slope of −0.11 dB SNR/test (∼0.9% word score/test), which accumulates to a total of 1.7 dB SNR (13%) between session start and end. The between-session learning curve was described more accurately with an exponential fit than with a linear fit. The between-test learning curve can be described equally well with a linear and an exponential fit. Conclusion: A robust between-test learning effect was observed, which could be accurately modeled using either a linear or exponential learning curve. Additionally, a between-session learning effect was evident and was best described by an exponential learning curve. This study provides an important handle for correcting these learning effects in future studies.

As more deaf and hard of hearing (DHH) students attend mainstream schools, understanding how physical and social environments can support their social inclusion becomes increasingly critical. Limited access to informal, unstructured peer interactions like those occurring during recess – important contexts for developing a social life at school – is a key challenge. This study makes three main contributions: (1) Synthesizing interdisciplinary research on DHH students' individual capabilities relevant to social participation through a narrative review, framed within school contexts using affordance theory. (2) Developing a novel affordance-based, conceptual framework that shows how DHH students’ opportunities for social participation arise from dynamic interactions between capabilities and school environment. (3) Creating a practical tool to support school evaluation and intervention planning by stakeholders without extensive DHH experience, and guiding future DHH affordance research. Findings demonstrate how DHH sensory, cognitive, and psychological capabilities interact with situational and environmental factors, including built spaces, group dynamics, and stigma. The framework also emphasizes how social experiences can, in turn, shape DHH capabilities over time. Supporting practical implementation, a DHH capability-environment matrix tool was developed, providing a visual means to map affordance relationships and systematically identify school barriers to social interaction. By reframing DHH inclusion through an affordance lens, this work shifts focus from individual limitations to systemic and environmental contributors to exclusion, situating deafness within a broader spectrum of diversity. The paper concludes with implications for advancing affordance research in environmental psychology and outlines directions for further development and evaluation of the matrix in school settings.

Objective: To determine correlations between speech recognition thresholds (SRTs) for everyday sentences compared to Matrix sentences and digits-in-noise (DIN) triplets. Design: Comparative analysis of SRTs across three speech materials in both cochlear implant (CI) users and typical hearing (TH) listeners, using linear regression and analysis of covariance. Study Sample: 18 experienced CI users (mean age 63 ± 5 years) and 18 age-equivalent TH listeners (mean age 62 ± 12 years), all naive to the test materials. Results: SRTs of Matrix sentences and everyday sentences correlated significantly (R²: 0.81 for CI, 0.71 for TH), as did SRTs of DIN triplets and everyday sentences (R²: 0.42 for CI, 0.28 for TH). Regression slopes did not differ significantly between CI and TH groups in either comparison. However, intercepts differed significantly between the CI (−2.65) and TH (−6.70) groups for the DIN triplets, but not for the Matrix sentences. Slopes for the DIN triplets deviated significantly from unity for both groups. Conclusions: Dutch/Flemish Matrix sentence SRTs closely correlate with everyday sentence SRTs for both CI users and TH listeners, establishing it as a reliable alternative for repeated assessment. DIN triplet SRTs showed weaker correlations with everyday sentences and with significant intercept differences between groups.

Objective and Design: With this cross-sectional study, we aimed to assess whether cochlear implant (CI) users have different occupational well-being than individuals with hearing loss (HL) without CI (HL group) and those with typical hearing (TH). We used validated questionnaires to assess all outcomes. Study sample: We included 98 CI users (mean age 51 y), 52 HL group participants (mean age 49 y) and 54 TH group participants (mean age 46 y). Results: Capabilities, physical and psychosocial working conditions were similar overall across the three groups. However, compared to the HL group, the CI group had significantly better outcomes on a range of variables, reporting fewer psychosomatic symptoms, better health, higher acceptance of their HL, better verbal coping strategies, fewer interruptions during work, and lower perceived noise level. There were no variables indicating that CI users performed worse than their peers from the HL group. Conclusions: Overall, CI users show occupational well-being and capabilities comparable to those of other groups. However, CI users appear to be more advanced in their progress towards acceptance of their HL, use of verbal coping strategies, are better adjusted at work, and report better health than individuals with HL without a CI.

Background: Cochlear implant users (CI) experience degraded speech intelligibility (SI) in noise. A contralateral hearing aid (HA) benefits listening in noise, and directional microphones and directivity steering can further enhance SI.Objectives: Four directional microphones were evaluated for bimodal listeners, including a monaural and binaural broadband front-facing beamformer (BFM and BFB) and a novel monaural and binaural narrowband side-beamformer (BFMS, BFBS). Broadband directivity steering (DS) was also evaluated. Methods: BFM, BFB, and DS were tested in diffuse noise with speech administered frontally or to the HA side (S0Ndif and SHANdif). BFMS and BFBS were tested with speech presented on the CI side and noise on the HA side or vice versa (SCINHA, SHANCI). SI was assessed by determining speech reception thresholds (SRTs). Results: In the S0Ndif condition, BFB significantly improved SI by 2.9 dB SNR and BFM by 1.3 dB SNR, but not significantly. In the SHANdif condition, BFM and BFB did not benefit SI, but DS improved SI by 3.6 dB. BFBS significantly improved SI by 1.1 dB SNR, but BFMS was ineffective. Conclusion: Binaural beamformers outperform their monaural counterparts. The novel BFBS is a promising technique for bimodal listeners.

Objective and design: This cross-sectional study aimed to compare occupational performance of cochlear implant (CI) users to that of adults with hearing impairment without CI and those with normal hearing (NH). We used the Amsterdam Checklist for Hearing and Work to assess job characteristics, hearing activities, need for recovery and other outcomes. Study sample: We included 204 adults: 98 CI users (mean age 51), 52 participants with hearing impairment, without CI (HI group, mean age 49) and 54 participants with NH (NH group, mean age 46). Results: Job characteristics were similar between the groups, but the CI and HI groups were significantly more likely to report (effortful) communication in noise compared to the NH group. Need for recovery was significantly higher in the HI than in the NH group, but the CI and NH groups showed no significant difference. The CI group needed less guidance in managing their hearing loss in the workplace than the HI group did. Conclusions: The relatively favourable outcomes for CI users in need for recovery and reduced need for guidance at work may be due to the extensive training and counselling they received as part of their rehabilitation program.

Objective: Measuring listening effort using pupillometry is challenging in cochlear implant (CI) users. We assess three validated speech tests (Matrix, LIST, and DIN) to identify the optimal speech material for measuring peak-pupil-dilation (PPD) in CI users as a function of signal-to-noise ratio (SNR). Design: Speech tests were administered in quiet and two noisy conditions, namely at the speech recognition threshold (0 dB re SRT), i.e. the SNR where speech intelligibility (SI) was 50%, and at a more favourable SNR of +6 dB re SRT. PPDs and subjective ratings of effort were obtained. Study sample: Eighteen unilaterally implanted CI users. Results: LIST sentences revealed significantly different PPDs between +6 and 0 dB re SRT and DIN triplets between quiet and +6 dB re SRT. PPDs obtained with the Matrix test were independent of SNR and yielded large PPDs and high subjective ratings even in quiet. Conclusions: PPD is a sensitive measure for listening effort when processing LIST sentences near 0 dB re SRT and when processing DIN triplets at more favourable listening conditions around +6 dB re SRT. PPDs obtained with the Matrix test were insensitive to SNR, likely because it is demanding for CI users even in quiet.

Objectives: Cochlear implants (CIs) are the primary treatment for severe-to-profound hearing loss. For CI users, speech intelligibility (SI) is often excellent in quiet yet degrades dramatically in background noise. Scientific and clinical testing of the effects of noise on SI is routinely performed with speech-in-noise tests. The sensitivity of these tests to signal to noise ratio depends on the slope of their psychometric curve. This slope is not always known for CI users, and direct comparisons between typical hearing (TH) listeners and CI users are lacking. Design: We present a comparative study of a digit test (DIN), a Matrix sentence test, and an everyday sentence test (LIST) for a group of CI users and TH listeners, with use of word (digit) and sentence (triplet) scoring in the free field. We report descriptive statistics and effect size measures of the psychometric slope and the speech reception threshold (SRT) for each speech test. Results: For CI users, the slopes of the psychometric curve were significantly shallower and SRTs significantly higher than those of TH listeners. The shallowest slope was seen with the Matrix test. However, the small variances of the slope and the SRT resulted in effect size estimates that fell between those of the other two tests. The DIN test was associated with steeply sloped psychometric curves with low variance. The scoring method did not substantially affect slopes and SRTs for the DIN test and LIST sentences, but word scoring resulted in shallow slopes and substantially worse SRTs for CI users. Conclusions: The DIN test stood out in this study as an attractive speech-in-noise test for CI users, with steep slopes and low variance in slopes and SRTs among participants. Digit and keyword scoring appear to be viable options for the DIN test and LIST sentences, respectively, potentially increasing the number of available test items. For the Matrix test, sentence scoring yielded shallow slopes and deteriorated SI, especially for the CI group. We recommend word scoring for the Dutch-Flemish Matrix test.

Objectives: – Cochlear implantation is the standard of care for severe-to-profound hearing loss in the Netherlands. Cochlear implants (CIs) generally perform well in quiet conditions, but speech understanding in an environment with reverberations remains difficult. This study aimed to minimize the amount of reverberation present in a speech signal by using novel artificial-intelligence-based algorithms created for use in CIs. Design: – A prospective crossover study was performed, which included 15 CI users, with each participant being their own control. Two versions of the algorithm were tested: one version that focused on late reverberations (DNN-WPE) and another version that additionally minimized early reverberation with a post-filter (DNN-WPEPF). These two algorithms were tested by performing speech intelligibility tests with percentage correct as the outcome measure. The Flemish/Dutch Matrix test was used for speech intelligibility testing. Six different conditions were measured: clean speech (no reverberation), clean speech processed with both algorithms, reverberated speech, and reverberated speech processed by both algorithms. In addition, subjective ratings were performed to assess how the participant perceived the processed sound. These subjective ratings were performed by pairwise comparisons of the aforementioned conditions regarding listening effort, naturalness, and speech intelligibility. Results: – The speech intelligibility scores revealed a statistically significant average improvement of 11% when reverberated speech was processed with DNN-WPE (p < 0.001) and 17% when processed with DNN-WPEPF (p < 0.001). Moreover, the benefit of DNN-WPEPF was significantly greater than the benefit of DNN-WPE (p = 0.018). Both algorithms did not significantly affect speech intelligibility when no reverberation was present (p > 0.05). The outcomes of the three subjective ratings complement the speech intelligibility scores. Speech dereverberated with either algorithm was significantly preferred over reverberated speech for all three outcomes (listening effort, naturalness, and speech intelligibility). Moreover, speech dereverberated with DNN-WPEPF was significantly preferred over speech dereverberated with DNN-WPE. Conclusions: – This study revealed that the DNN-WPE and DNN-WPEPF dereverberation algorithms had benefits for CI users regarding speech intelligibility and subjective ratings. These algorithms did not affect the clean speech, showing that they can be switched on in quiet situations without background noise. Further developments are required to implement the algorithms in real time on the CI processor, and more research is needed to assess them under more realistic listening conditions.

Objectives:
The substantial variability in speech perception outcomes after cochlear implantation complicates efforts to develop valid predictive models of these outcomes. Existing predictive regression models are too unreliable for clinical application, possibly because speech intelligibility (SI) after cochlear implant (CI) rehabilitation is often based on a limited number of assessments. The development of SI after CI has rarely been detailed, although knowing the shape of the learning curve can potentially improve predictive modeling. Knowing the learning curve after CI could also aid in setting expectations about SI immediately after implantation, and the duration of rehabilitation. The current objectives were to construct learning curves to estimate baseline SI at 1 week (B), maximal SI after rehabilitation (M), and rehabilitation time (time to reach 80% of the learning effect; t[M − B]80%), and to subsequently deploy these outcomes for multiple-regression modeling to predict CI outcomes.

Design:
To assess rehabilitation after cochlear implantation, we retrospectively fitted learning curves using clinically available SI assessments from 533 postlingually deaf, unilaterally implanted adults. SI was assessed with consonant-vowel-consonant words (CVC) in quiet, with phoneme score as the outcome measure. Participants were followed for up to 4 years, with SI measurements collected at fixed intervals. SI was commonly assessed 1, 2, 4, and 8 weeks after device activation. B, M, and t(M − B)80% were determined from the fitted learning curves. Predictive multiple-regression analyses were performed on these three outcome measures based on eight previously identified preoperative demographic and audiometric predictor variables: age at implantation, duration of severe-to-profound hearing loss, best-aided CVC phoneme score (in the free field), unaided ipsilateral and contralateral residual hearing and CVC phoneme scores (measured with headphones), and education type (regular or special education).

Results:
At 1 week after CI activation, raw phoneme scores had increased from 40% preoperatively (best-aided condition) to 51%, with further improvement to approximately 78% at 4 years. SI increased significantly until 1 year after activation and then plateaued. Fitted learning curves supported better estimates of these parameters, showing that average baseline SI at 1 week after CI activation was 51%, increasing to 85% after rehabilitation. The asymptotic score exceeded the raw average after 4 years because many cases had not yet plateaued. The median t(M − B)80% was 1.5 months. Predictive modeling identified duration of hearing loss, age at implantation, best-aided CVC phoneme score, and education type as the most robust predictors for postoperative SI. Despite the statistically significant correlations, however, the combined predictive value was ~19% for B, 10% for M, and 2% for t(M − B)80%.

Conclusions:
This study is among the few to generate detailed learning curves after cochlear implantation. By including clinical SI measures in the earliest rehabilitation period, we report a median rehabilitation time with CI of 1.5 months. This implied rapid learning effect emphasizes the value of monitoring SI in the first few weeks after rehabilitation. According to multiple-regression analyses, the most commonly used preoperative variables correlated significantly with postoperative outcomes, but with limited predictive value for the clinic. By fitting learning curves through data reported in the literature, we show that the increase in SI during rehabilitation is an important predictor for t(M − B)80%.

Objectives:
We investigated whether listening effort is dependent on task difficulty for cochlear implant (CI) users when using the Matrix speech-in-noise test. To this end, we measured peak pupil dilation (PPD) at a wide range of signal to noise ratios (SNR) by systematically changing the noise level at a constant speech level, and vice versa.

Design:
A group of mostly elderly CI users performed the Dutch/Flemish Matrix test in quiet and in multitalker babble at different SNRs. SNRs were set relative to the speech-recognition threshold (SRT), namely at SRT, and 5 and 10 dB above SRT (0 dB, +5 dB, and +10 dB re SRT). The latter 2 conditions were obtained by either varying speech level (at a fixed noise level of 60 dBA) or by varying noise level (with a fixed speech level). We compared these PPDs with those of a group of typical hearing (TH) listeners. In addition, listening effort was assessed with subjective ratings on a Likert scale.

Results:
PPD for the CI group did not significantly depend on SNR, whereas SNR significantly affected PPDs for TH listeners. Subjective effort ratings depended significantly on SNR for both groups. For CI users, PPDs were significantly larger, and effort was rated higher when speech was varied, and noise was fixed for CI users. By contrast, for TH listeners effort ratings were significantly higher and performance scores lower when noise was varied, and speech was fixed.

Conclusions:
The lack of a significant effect of varying SNR on PPD suggests that the Matrix test may not be a feasible speech test for measuring listening effort with pupillometric measures for CI users. A rating test appeared more promising in this population, corroborating earlier reports that subjective measures may reflect different dimensions of listening effort than pupil dilation. Establishing the SNR by varying speech or noise level can have subtle, but significant effects on measures of listening effort, and these effects can differ between TH listeners and CI users.

Introduction: Cochlear implantation is the standard treatment for severe to profound hearing loss. While cochlear implant (CI) users can communicate effectively in quiet environments, speech understanding in noise remains challenging. Bimodal hearing, combining a CI in one ear and a hearing aid (HA) in the other, has shown advantages over unilateral electrical hearing, especially for speech understanding in noisy conditions. Beamforming is a technique used to improve speech understanding in noise by detecting sound direction and enhancing frontal (speech) sounds while attenuating background noise. One specific beamformer, Stereozoom, combines signals from microphones in both ears to create a focused beam toward the front resulting in a binaural beamformer (BB), in order to improve speech intelligibility in noise for bilateral and bimodal CI users. Methods: A prospective crossover study involving 17 bimodal CI users was conducted, and participants were tested with various device configurations (CI, HA, CI + HA) with and without BB. Speech recognition testing with the Dutch/Flemish matrix test was performed in a sound-attenuated booth with diffuse noise to simulate realistic listening conditions. Results: The results showed a statistically significant benefit of bimodal hearing over the CI configuration and showed a statistical significant benefit of BB for the CI and CI + HA configuration. The benefit of BB in the HA configuration was not statistically significant probably due to the higher variance. The benefit of BB in the three configurations did not differ statistically significant. Conclusion: In conclusion, bimodal hearing offers advantages for speech understanding in noise for CI users. BB provides a benefit in various device configurations, leading to improved speech intelligibility when speech comes from the front in challenging listening environments.