Objective Assessment of Binaural Benefit from Acoustical Treatment in Real Primary School Classrooms.

Providing students with an adequate acoustic environment is crucial for ensuring speech intelligibility in primary school classrooms. Two main approaches to control acoustics in educational facilities consist of reducing background noise and late reverberation. Prediction models for speech intelligibility have been developed and implemented to evaluate the effects of these approaches. In this study, two versions of the Binaural Speech Intelligibility Model (BSIM) were used to predict speech intelligibility in realistic spatial configurations of speakers and listeners, considering binaural aspects. Both versions shared the same binaural processing and speech intelligibility backend processes but differed in the pre-processing of the speech signal. An Italian primary school classroom was characterized in terms of acoustics before (reverberation, T20 = 1.6 ± 0.1 s) and after (T20 = 0.6 ± 0.1 s) an acoustical treatment to compare BSIM predictions to well-established room acoustic measures. With shorter reverberation time, speech clarity and definition improved, as well as speech recognition thresholds (SRTs) (by up to ~6 dB), particularly when the noise source was close to the receiver and an energetic masker was present. Conversely, longer reverberation times resulted (i) in poorer SRTs (by ~11 dB on average) and (ii) in an almost non-existent spatial release from masking at an angle (SRM).

Spatio-temporal Integration of Speech Reflections in Hearing-Impaired Listeners.

Speech recognition in rooms requires the temporal integration of reflections which arrive with a certain delay after the direct sound. It is commonly assumed that there is a certain temporal window of about 50-100 ms, during which reflections can be integrated with the direct sound, while later reflections are detrimental to speech intelligibility. This concept was challenged in a recent study by employing binaural room impulse responses (RIRs) with systematically varied interaural phase differences (IPDs) and amplitude of the direct sound and a variable number of reflections delayed by up to 200 ms. When amplitude or IPD favored late RIR components, normal-hearing (NH) listeners appeared to be capable of focusing on these components rather than on the precedent direct sound, which contrasted with the common concept of considering early RIR components as useful and late components as detrimental. The present study investigated speech intelligibility in the same conditions in hearing-impaired (HI) listeners. The data indicate that HI listeners were generally less able to "ignore" the direct sound than NH listeners, when the most useful information was confined to late RIR components. Some HI listeners showed a remarkable inability to integrate across multiple reflections and to optimally "shift" their temporal integration window, which was quite dissimilar to NH listeners. This effect was most pronounced in conditions requiring spatial and temporal integration and could provide new challenges for individual prediction models of binaural speech intelligibility.

Development and evaluation of the Cantonese matrix sentence test.

OBJECTIVE: To develop the Cantonese matrix (YUEmatrix) test according to the international standard procedure and examine possible different outcomes in another tonal language. DESIGN: A 50-word Cantonese base-matrix was established. Word-specific speech recognition functions, speech recognition thresholds (SRT), and slopes were obtained. The speech material was homogenised in intelligibility by applying level corrections up to ± 3 dB. Subsequently, the YUEmatrix test was evaluated in five aspects: training effect, test-list equivalence, test-retest reliability, establishment of reference data for normal-hearing Cantonese-speakers, and comparison with the Cantonese-Hearing-In-Noise-Test. STUDY SAMPLE: Overall, 64 normal-hearing native Cantonese-speaking listeners. RESULTS: SRT measurements with adaptive procedures resulted in a reference SRT of -9.7 ± 0.7 dB SNR for open-set and -11.1 ± 1.2 dB SNR for the closed-set response format. Fixed SNR measurements suggested a test-specific speech intelligibility function slope of 15.5 ± 0.7%/dB. Seventeen 10-sentences base test lists were confirmed to be equivalent with respect to speech intelligibility. Training effect was not observed after two measurements of 20-sentences lists. CONCLUSIONS: The YUEmatrix yields comparable results to matrix tests in other languages including Mandarin. Level adjustments to homogenise sentences appear to be less effective for tonal languages than for most other languages developed so far.

Inference of the distortion component of hearing impairment from speech recognition by predicting the effect of the attenuation component.

OBJECTIVE: A model-based determination of the average supra-threshold ("distortion") component of hearing impairment which limits the benefit of hearing aid amplification. DESIGN: Published speech recognition thresholds (SRTs) were predicted with the framework for auditory discrimination experiments (FADE), which simulates recognition processes, the speech intelligibility index (SII), which exploits frequency-dependent signal-to-noise ratios (SNR), and a modified SII with a hearing-loss-dependent band importance function (PAV). Their attenuation-component-based prediction errors were interpreted as estimates of the distortion component. STUDY SAMPLE: Unaided SRTs of 315 hearing-impaired ears measured with the German matrix sentence test in stationary noise. RESULTS: Overall, the models showed root-mean-square errors (RMSEs) of 7 dB, but for steeply sloping hearing loss FADE and PAV were more accurate (RMSE = 9 dB) than the SII (RMSE = 23 dB). Prediction errors of FADE and PAV increased linearly with the average hearing loss. The consideration of the distortion component estimate significantly improved the accuracy of FADE's and PAV's predictions. CONCLUSIONS: The supra-threshold distortion component-estimated by prediction errors of FADE and PAV-seems to increase with the average hearing loss. Accounting for a distortion component improves the model predictions and implies a need for effective compensation strategies for supra-threshold processing deficits with increasing audibility loss.

Evaluation of Italian Simplified Matrix Test for Speech-Recognition Measurements in Noise.

This study aimed at the evaluation of a simplified Italian matrix test (SiIMax) for speech-recognition measurements in noise for adults and children. Speech-recognition measurements with adults and children were conducted to examine the training effect and to establish reference speech-recognition thresholds of 50% (SRT50) and 80% (SRT80) correct responses. Test-list equivalency was evaluated only with adults. Twenty adults and 96 children-aged between 5 and 10 years-participated. Evaluation measurements with the adults confirmed the equivalence of the test lists, with a mean SRT50 of -8.0 dB and a standard deviation of 0.2 dB across the test lists. The test-specific slope (the average of the list-specific slopes) was 11.3%/dB, with a standard deviation of 0.6%/dB. For both adults and children, only one test list of 14 phrases needs to be presented to account for the training effect. For the adults, adaptive measurements of the SRT50 and SRT80 showed mean values of -7.0 ± 0.6 and -4.5 ± 1.1 dB, respectively. For children, a slight influence of age on the SRT was observed. The mean SRT50s were -5.6 ± 1.2, -5.8 ± 1.2 and -6.6 ± 1.3 dB for the children aged 5-6, 7-8 and 9-10 years, respectively. The corresponding SRT80s were -1.5 ± 2.7, -3.0 ± 1.7 and -3.7 ± 1.4 dB. High test-retest reliabilities of 1.0 and 1.1 dB for the SRT80 were obtained for the adults and children, respectively. This makes the test suitable for accurate and reliable speech-recognition measurements.

Sensitivity and specificity of automatic audiological classification using expert-labelled audiological data and Common Audiological Functional Parameters.

OBJECTIVE: As a step towards the development of an audiological diagnostic supporting tool employing machine learning methods, this article aims at evaluating the classification performance of different audiological measures as well as Common Audiological Functional Parameters (CAFPAs). CAFPAs are designed to integrate different clinical databases and provide abstract representations of measures. DESIGN: Classification and evaluation of classification performance in terms of sensitivity and specificity are performed on a data set from a previous study, where statistical models of diagnostic cases were estimated from expert-labelled data. STUDY SAMPLE: The data set contains 287 cases. RESULTS: The classification performance in clinically relevant comparison sets of two competing categories was analysed for audiological measures and CAFPAs. It was found that for different audiological diagnostic questions a combination of measures using different weights of the parameters is useful. A set of four to six measures was already sufficient to achieve maximum classification performance which indicates that the measures contain redundant information. CONCLUSIONS: The current set of CAFPAs was confirmed to yield in most cases approximately the same classification performance as the respective optimum set of audiological measures. Overall, the concept of CAFPAs as compact, abstract representation of auditory deficiencies is confirmed.

Individual Aided Speech-Recognition Performance and Predictions of Benefit for Listeners With Impaired Hearing Employing FADE.

The benefit in speech-recognition performance due to the compensation of a hearing loss can vary between listeners, even if unaided performance and hearing thresholds are similar. To accurately predict the individual performance benefit due to a specific hearing device, a prediction model is proposed which takes into account hearing thresholds and a frequency-dependent suprathreshold component of impaired hearing. To test the model, the German matrix sentence test was performed in unaided and individually aided conditions in quiet and in noise by 18 listeners with different degrees of hearing loss. The outcomes were predicted by an individualized automatic speech-recognition system where the individualization parameter for the suprathreshold component of hearing loss was inferred from tone-in-noise detection thresholds. The suprathreshold component was implemented as a frequency-dependent multiplicative noise (mimicking level uncertainty) in the feature-extraction stage of the automatic speech-recognition system. Its inclusion improved the root-mean-square prediction error of individual speech-recognition thresholds (SRTs) from 6.3 dB to 4.2 dB and of individual benefits in SRT due to common compensation strategies from 5.1 dB to 3.4 dB. The outcome predictions are highly correlated with both the corresponding observed SRTs (R2 = .94) and the benefits in SRT (R2 = .89) and hence might help to better understand-and eventually mitigate-the perceptual consequences of as yet unexplained hearing problems, also discussed in the context of hidden hearing loss.

Clinical validation of the Russian Matrix test - effect of hearing loss, age, and noise level.

OBJECTIVE: To validate the Russian matrix sentence test (RUMatrix) for the assessment of speech recognition in quiet and in noise in clinical praxis. The effect of hearing impairment, age, and masking-noise level on speech recognition was examined. DESIGN: All participants underwent pure tone audiometry, a monosyllabic speech test in quiet, and speech recognition measurements with RUMatrix in quiet (SRTQ) and in noise (SRTN). STUDY SAMPLE: One hundred and forty-two listeners divided into four groups: 1. Young normal-hearing listeners, 2. Older normal-hearing listeners, 3. Young hearing-impaired listeners, and 4. Older hearing-impaired listeners. RESULTS: Significant differences between groups of listeners were found in the SRTQ and SRTN. A strong correlation between hearing threshold and SRTQ (R2=0.88, p < 0.001) indicates a strong link between speech recognition in quiet and audibility. The pure-tone average explained less variance in SRTN (R2=0.67, p < 0.001), pointing out an additional influence of suprathreshold distortion. A high test sensitivity of 0.99 was found for SRTN and SRTQ. The monosyllabic test had a low sensitivity (0.21), indicating that the test is not suitable for separating normal-hearing and hearing-impaired listeners. CONCLUSIONS: RuMatrix is a reliable speech recognition assessment tool with a high sensitivity and validity for the main aspects of hearing impairment.

Simulations with FADE of the effect of impaired hearing on speech recognition performance cast doubt on the role of spectral resolution.

Listeners with hearing impairment show sub-optimal processing of acoustic signals which affects their ability to recognize speech. In this contribution, three effective signal processing deficits are proposed to simulate sensorineural hearing impairment and their effect on simulated speech recognition performance is studied. Psychoacoustic and speech recognition experiments were simulated with the framework for auditory discrimination experiments (FADE). Loss in absolute hearing threshold was modeled as lower level limit, supra-threshold loss in envelope amplitude resolution as multiplicative noise, and reduced spectral resolution was simulated with an increase of the analysis bandwidth. Their effects on the speech recognition performance with the German matrix test in quiet and noise, the audiogram, and tone in (notched) noise detection experiments were systematically examined. The simulations indicate that each psychoacoustic experiment relates to at least one signal processing deficit. This indicates the possibility to determine individual model parameters from the outcome of psychoacoustic experiments. Moreover, absolute hearing thresholds yield the highest effects on simulated speech recognition thresholds, followed by supra-threshold loss in envelope amplitude resolution, and-to a much smaller degree-spectral resolution. A reduced spectral resolution only affected recognition performance in fluctuating masker for normal hearing thresholds, indicating its potential relevance for more complex listening conditions. In contrast to popular interpretations in the literature, the simulations reveal that reduced spectral resolution plays a minor role compared to a reduced envelope amplitude resolution in characterizing supra-threshold hearing loss at least in stationary noise.

Common Audiological Functional Parameters (CAFPAs) for single patient cases: deriving statistical models from an expert-labelled data set.

Objective: Statistical knowledge about many patients could be exploited using machine learning to provide supporting information to otolaryngologists and other hearing health care professionals, but needs to be made accessible. The Common Audiological Functional Parameters (CAFPAs) were recently introduced for the purpose of integrating data from different databases by providing an abstract representation of audiological measurements. This paper aims at collecting expert labels for a sample database and to determine statistical models from the labelled data set.Design: By an expert survey, CAFPAs as well as labels for audiological findings and treatment recommendations were collected for patients from the database of Hörzentrum Oldenburg.Study sample: A total of 287 single patient cases were assessed by twelve highly experienced audiological experts.Results: The labelled data set was used to derive probability density functions for categories given by the expert labels. The collected data set is suitable for estimating training distributions due to realistic variability contained in data for different, distinct categories. Suitable distribution functions were determined. The derived training distributions were compared regarding different audiological questions.Conclusions: The method-expert survey, sorting data into categories, and determining training distributions - could be extended to other data sets, which could then be integrated via the CAFPAs and used in a classification task.

Measurement and Prediction of Binaural-Temporal Integration of Speech Reflections.

For speech intelligibility in rooms, the temporal integration of speech reflections is typically modeled by separating the room impulse response (RIR) into an early (assumed beneficial for speech intelligibility) and a late part (assumed detrimental). This concept was challenged in this study by employing binaural RIRs with systematically varied interaural phase differences (IPDs) and amplitude of the direct sound and a variable number of reflections delayed by up to 200 ms. Speech recognition thresholds in stationary noise were measured in normal-hearing listeners for 86 conditions. The data showed that direct sound and one or several early speech reflections could be perfectly integrated when they had the same IPD. Early reflections with the same IPD as the noise (but not as the direct sound) could not be perfectly integrated with the direct sound. All conditions in which the dominant speech information was within the early RIR components could be well predicted by a binaural speech intelligibility model using classic early/late separation. In contrast, when amplitude or IPD favored late RIR components, listeners appeared to be capable of focusing on these components rather than on the precedent direct sound. This could not be modeled by an early/late separation window but required a temporal integration window that can be flexibly shifted along the RIR.

Common Audiological Functional Parameters (CAFPAs): statistical and compact representation of rehabilitative audiological classification based on expert knowledge.

OBJECTIVE: As a step towards objectifying audiological rehabilitation and providing comparability between different test batteries and clinics, the Common Audiological Functional Parameters (CAFPAs) were introduced as a common and abstract representation of audiological knowledge obtained from diagnostic tests. DESIGN: Relationships between CAFPAs as an intermediate representation between diagnostic tests and audiological findings, diagnoses and treatment recommendations (summarised as "diagnostic cases") were established by means of an expert survey. Expert knowledge was collected for 14 given categories covering different diagnostic cases. For each case, the experts were asked to indicate expected ranges of diagnostic test outcomes, as well as traffic light-encoded CAFPAs. STUDY SAMPLE: Eleven German experts in the field of audiological rehabilitation from Hanover and Oldenburg participated in the survey. RESULTS: Audiological findings or treatment recommendations could be distinguished by a statistical model derived from the experts' answers for CAFPAs as well as audiological tests. CONCLUSIONS: The CAFPAs serve as an abstract, comprehensive representation of audiological knowledge. If more detailed information on certain functional aspects of the auditory system is required, the CAFPAs indicate which information is missing. The statistical graphical representations for CAFPAs and audiological tests are suitable for audiological teaching material; they are universally applicable for real clinical databases.

Construction and evaluation of the Mandarin Chinese matrix (CMNmatrix) sentence test for the assessment of speech recognition in noise.

OBJECTIVE: Development of the Mandarin Chinese matrix (CMNmatrix) sentence test for speech intelligibility measurements in noise according to the international standard procedure. DESIGN: A 50-word base matrix representing the distribution of phonemes and lexical tones of spoken Mandarin was established. Hundred sentences capturing all the co-articulations of two consecutive words were recorded. Word-specific speech recognition functions, speech reception thresholds (SRT: signal-to-noise ratio (SNR), that provides 50% speech intelligibility) and slopes were obtained from measurements at fixed SNRs. The speech material was homogenised in intelligibility by applying level corrections up to ± 2 dB. Subsequently, the CMNmatrix test was evaluated, the comparability of test lists was measured at two fixed SNRs. To investigate the training effect and establish the reference data, speech recognition was measured adaptively. STUDY SAMPLE: Overall, the study sample contained 80 normal-hearing native Mandarin-speaking listeners. RESULTS: Multi-centre evaluation measurements confirmed that test lists are equivalent in intelligibility, with a mean SRT of -10.1 ± 0.1 dB SNR and a slope of 13.1 ± 0.9 %/dB. The reference SRT is -9.3 ± 0.8 and -11.2 ± 1.2 dB SNR for the open- and closed-set response format, respectively. CONCLUSION: The CMNmatrix test is suitable for accurate and internationally comparable speech recognition measurements in noise.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

Sentence Recognition Prediction for Hearing-impaired Listeners in Stationary and Fluctuation Noise With FADE: Empowering the Attenuation and Distortion Concept by Plomp With a Quantitative Processing Model.

To characterize the individual patient's hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The "typical" audiogram shapes from Bisgaard et al with or without a "typical" level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only.

Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise.

Vocabulary size has been suggested as a useful measure of "verbal abilities" that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18-35 years) and 22 older (60-78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults' poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access.

Genes Encoding Cucumber Full-Size ABCG Proteins Show Different Responses to Plant Growth Regulators and Sclareolide.

Full-size members of the ABCG (ATP-binding cassette, subfamily G) subfamily of ABC transporters have been found only in plants and fungi. The plant genes encoding full-size ABCGs identified so far appeared to be differentially regulated under various environmental constraints, plant growth regulators, and microbial elicitors, indicating a broad functional role of these proteins in plant responses to abiotic and biotic stress. Nevertheless, the structure and physiological function of full-size ABCGs in many plant species are still unknown. We have recently identified 16 genes encoding full-size ABCG proteins in cucumber and found that the transcripts of two of them, CsABCG36 (CsPDR8) and CsABCG40 (CsPDR12), are most abundant in roots and are significantly affected by phytohormones and auxin herbicide. In this study, we analyzed the structure and phylogeny of all the full-size cucumber ABCG transporters and studied the organ expression profiles of the remaining 14 CsABCG genes. In addition, we investigated the effect of different plant growth regulators and the diterpene sclareolide on CsABCG expression in cucumber roots. Until now, the full-size plant ABCG transporters have been grouped into five different clusters. The new phylogenetic analysis of full-size ABCGs from model plants and cucumber clustered these proteins into six different subgroups. Interestingly, the expression profiles of cucumber ABCG genes assigned to the same clusters were not correlated, suggesting functional diversification or different regulatory mechanisms of the full-size cucumber ABCG proteins.

A simulation framework for auditory discrimination experiments: Revealing the importance of across-frequency processing in speech perception.

A framework for simulating auditory discrimination experiments, based on an approach from Schädler, Warzybok, Hochmuth, and Kollmeier [(2015). Int. J. Audiol. 54, 100-107] which was originally designed to predict speech recognition thresholds, is extended to also predict psychoacoustic thresholds. The proposed framework is used to assess the suitability of different auditory-inspired feature sets for a range of auditory discrimination experiments that included psychoacoustic as well as speech recognition experiments in noise. The considered experiments were 2 kHz tone-in-broadband-noise simultaneous masking depending on the tone length, spectral masking with simultaneously presented tone signals and narrow-band noise maskers, and German Matrix sentence test reception threshold in stationary and modulated noise. The employed feature sets included spectro-temporal Gabor filter bank features, Mel-frequency cepstral coefficients, logarithmically scaled Mel-spectrograms, and the internal representation of the Perception Model from Dau, Kollmeier, and Kohlrausch [(1997). J. Acoust. Soc. Am. 102(5), 2892-2905]. The proposed framework was successfully employed to simulate all experiments with a common parameter set and obtain objective thresholds with less assumptions compared to traditional modeling approaches. Depending on the feature set, the simulated reference-free thresholds were found to agree with-and hence to predict-empirical data from the literature. Across-frequency processing was found to be crucial to accurately model the lower speech reception threshold in modulated noise conditions than in stationary noise conditions.

An Italian matrix sentence test for the evaluation of speech intelligibility in noise.

OBJECTIVE: Development of an Italian matrix sentence test for the assessment of speech intelligibility in noise. DESIGN: The development of the test included the selection, recording, optimization with level adjustment, and evaluation of speech material. The training effect was assessed adaptively during the evaluation measurements with six lists of 20 sentences, using open- and closed-set response formats. Reference data were established for normal-hearing listeners with adaptive measurements. Equivalence of the test lists was investigated using the open-set response format at three signal-to-noise ratios (SNRs). STUDY SAMPLE: A total of 55 normal-hearing Italian mother-tongue listeners. RESULTS: The evaluation measurements at fixed SNRs resulted in a mean speech reception threshold (SRT) of -7.3 ± 0.2 dB SNR and slope of 13.3 ± 1.2 %/dB. The major training effect of 1.5 dB was observed for the first two consecutive measurements. Mean SRTs of -6.7 ± 0.7 dB SNR and -7.4 ± 0.7 dB SNR were found from the third to the sixth adaptive measurement for open- and closed-set test response formats, respectively. CONCLUSIONS: A good agreement has been found between the SRTs and slope and those of other matrix tests. Since sentences are difficult to memorize, the Italian matrix test is suitable for repeated measurements.

How much does language proficiency by non-native listeners influence speech audiometric tests in noise?

OBJECTIVE: The current study investigates the extent to which the linguistic complexity of three commonly employed speech recognition tests and second language proficiency influence speech recognition thresholds (SRTs) in noise in non-native listeners. DESIGN: SRTs were measured for non-natives and natives using three German speech recognition tests: the digit triplet test (DTT), the Oldenburg sentence test (OLSA), and the Göttingen sentence test (GÖSA). STUDY SAMPLE: Sixty-four non-native and eight native listeners participated. RESULTS: Non-natives can show native-like SRTs in noise only for the linguistically easy speech material (DTT). Furthermore, the limitation of phonemic-acoustical cues in digit triplets affects speech recognition to the same extent in non-natives and natives. For more complex and less familiar speech materials, non-natives, ranging from basic to advanced proficiency in German, require on average 3-dB better signal-to-noise ratio for the OLSA and 6-dB for the GÖSA to obtain 50% speech recognition compared to native listeners. CONCLUSIONS: In clinical audiology, SRT measurements with a closed-set speech test (i.e. DTT for screening or OLSA test for clinical purposes) should be used with non-native listeners rather than open-set speech tests (such as the GÖSA or HINT), especially if a closed-set version in the patient's own native language is available.