148 research outputs found

    Sources of uncertainty in Greenland surface mass balance in the 21st century

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    The surface mass balance (SMB) of the Greenland ice sheet is subject to considerable uncertainties that complicate predictions of sea level rise caused by climate change. We examine the SMB of the Greenland ice sheet in the 21st century with the Bergen Snow Simulator (BESSI) surface energy and mass balance model. To estimate the uncertainty of the SMB, we conduct simulations for four greenhouse gas emission scenarios using the output of a wide range of Earth system models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to force BESSI. In addition, the uncertainty of the SMB simulation is estimated by using 16 different parameter sets in our SMB model. The median SMB across ESMs and parameter sets, integrated over the ice sheet, decreases over time for every emission scenario. As expected, the decrease in SMB is stronger for higher greenhouse gas emissions. The regional distribution of the resulting SMB shows the most substantial SMB decrease in western Greenland for all ESMs, whereas the differences between the ESMs are most pronounced in the north and around the equilibrium line. Temperature and precipitation are the input variables of the snow model that have the largest influence on the SMB and the largest differences between ESMs. In our ensemble, the range of uncertainty in the SMB is greater than in previous studies that used fewer ESMs as forcing. An analysis of the different sources of uncertainty shows that the uncertainty caused by the different ESMs for a given scenario is larger than the uncertainty caused by the climate scenarios. In comparison, the uncertainty caused by the snow model parameters is negligible, leaving the uncertainty of the ESMs as the main reason for SMB uncertainty.publishedVersio

    Model simulations of masked thresholds for tones in dichotic noise maskers (A)

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    The study of masked thresholds in dichotic noise maskers is important for understanding the processing in binaural hearing. To simulate these thresholds a psychoacoustically motivated perception model was used [T. Dau et al. (1995). ``A quantitative model of the ``effective'' signal processing in the auditory system: I. Model structure,'' submitted to J. Acoust. Soc. Am.]. This model, which has been successfully applied to several monaural psychoacoustical experiments, was extended by an additional binaural processing unit. It consists of a filterbank, half-wave rectifier, low-pass filter, and adaptation loops, which model the temporal processing. The binaural processing unit detects the interaural correlation and makes decisions based on the difference between the signals from both ears. Masked thresholds in the NoS and NSo configurations, obtained as a function of noise masker frequency and bandwidth, were simulated and compared to new experimental measurements. The dependence on interaural delay and interaural decorrelation of the noise masker was also modeled and compared to data in the literature. In general, model simulations agree well with the main features seen in the measurements. [Work supported by DFG (Ho 1627/1-1) and by NIDCD (Grant DC00100).

    The quest for ecological validity in hearing science: what it is, why it matters, and how to advance it

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    Ecological validity is a relatively new concept in hearing science. It has been cited as relevant with increasing frequency in publications over the past 20 years, but without any formal conceptual basis or clear motive. The sixth Eriksholm Workshop was convened to develop a deeper understanding of the concept for the purpose of applying it in hearing research in a consistent and productive manner. Inspired by relevant debate within the field of psychology, and taking into account the World Health Organization’s International Classification of Functioning, Disability, and Health framework, the attendees at the workshop reached a consensus on the following definition: “In hearing science, ecological validity refers to the degree to which research findings reflect real-life hearing-related function, activity, or participation.” Four broad purposes for striving for greater ecological validity in hearing research were determined: A (Understanding) better understanding the role of hearing in everyday life; B (Development) supporting the development of improved procedures and interventions; C (Assessment) facilitating improved methods for assessing and predicting ability to accomplish real-world tasks; and D (Integration and Individualization) enabling more integrated and individualized care. Discussions considered the effects of variables and phenomena commonly present in hearing-related research on the level of ecological validity of outcomes, supported by examples from a few selected outcome domains and for different types of studies. Illustrated with examples, potential strategies were offered for promoting a high level of ecological validity in a study and for how to evaluate the level of ecological validity of a study. Areas in particular that could benefit from more research to advance ecological validity in hearing science include: (1) understanding the processes of hearing and communication in everyday listening situations, and specifically the factors that make listening difficult in everyday situations; (2) developing new test paradigms that include more than one person (e.g., to encompass the interactive nature of everyday communication) and that are integrative of other factors that interact with hearing in real-life function; (3) integrating new and emerging technologies (e.g., virtual reality) with established test methods; and (4) identifying the key variables and phenomena affecting the level of ecological validity to develop verifiable ways to increase ecological validity and derive a set of benchmarks to strive for

    Evaluating a distortion-weighted glimpsing metric for predicting binaural speech intelligibility in rooms

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    A distortion-weighted glimpse proportion metric (BiDWGP) for predicting binaural speech intelligibility were evaluated in simulated anechoic and reverberant conditions, with and without a noise masker. The predictive performance of BiDWGP was compared to four reference binaural intelligibility metrics, which were extended from the Speech Intelligibility Index (SII) and the Speech Transmission Index (STI). In the anechoic sound field, BiDWGP demonstrated high accuracy in predicting binaural intelligibility for individual maskers (ρ ≥ 0.95) and across maskers (ρ ≥ 0.94). The reference metrics however performed less well in across-masker prediction (0.54 ≤ ρ ≤ 0.86) despite reasonable accuracy for individual maskers. In reverberant rooms, BiDWGP was more stable in all test conditions (ρ ≥ 0.87) than the reference metrics, which showed different predictive patterns: the binaural STIs were more robust for the stationary than for the fluctuating noise masker, whilst the binaural SII displayed the opposite behaviour. The study shows that the new BiDWGP metric can provide similar or even more robust predictive power than the current standard metric

    Wenn die Hörgeräte laufen lernen ...

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    Modellierung der Reliabilität des Freiburger Einsilbertests in Ruhe mit der verallgemeinerten Binomialverteilung: Hat der Freiburger Einsilbertest 29 Wörter pro Liste?

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    Ein Sprachtest, und damit auch der Freiburger Einsilbertest, kann als Bernoulli-Experiment modelliert werden. Auf diese Weise können quantitative Aussagen zu seiner Reliabilität mit einer Binomialverteilung berechnet werden. Dabei wird in der Regel die gleiche Wahrscheinlichkeit für die Erkennung jedes Testwortes angenommen. Da die Wörter innerhalb einer Liste des Freiburger Einsilbertests jedoch unterschiedlich gut oder schlecht zu verstehen sind, ist eine Modellierung mit der verallgemeinerten Binomialverteilung sinnvoll. Dies führt zu einem kleineren Konfidenzintervall als bei der Verwendung der einfachen Binomialverteilung. Die Varianz der verallgemeinerten Binomialverteilung für Testlisten des Freiburger Einsilbertests mit 20 Wörtern kann durch diejenige Varianz einer einfachen Binomialverteilung angenähert werden, die auf Testlisten mit 29 Wörtern mit gleichem Wortverstehen beruht.Every speech test can be modelled as a Bernoulli experiment; this also applies to the Freiburg monosyllabic speech test. The model enables quantitative calculation of the reliability based on the binomial distribution. Generally, the same probability for the recognition of each test word is assumed. Since the recognition of words within test lists of the Freiburg monosyllabic speech test differs, modelling with the Poisson binomial distribution is reasonable. The Poisson binomial distribution results in a narrower confidence interval than the simple binomial distribution. The variance of the Poisson binomial distribution for test lists of the Freiburg monosyllabic speech test with 20 words can be approximated using the variance of the simple binomial distribution based on test lists with 29 equally-recognizable words

    Modeling the reliability of the Freiburg monosyllabic speech test in quiet with the Poisson binomial distribution. Does the Freiburg monosyllabic speech test contain 29 words per list?

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    Every speech test can be modeled as a Bernoulli experiment; this also applies to the Freiburg monosyllabic speech test. The model enables a quantitative calculation of the reliability based on the binomial distribution. Generally, the same probability is assumed for the recognition of each test word. Since the recognition of words within test lists of the Freiburg monosyllabic speech test differs, modeling with the Poisson binomial distribution is reasonable, and results in a narrower confidence interval than the simple binomial distribution. The variance of the Poisson binomial distribution for test lists of the Freiburg monosyllabic speech test with 20 words can be approximated using the variance of the simple binomial distribution based on test lists with 29 equally-recognizable words

    Modellierung der Test-Retest-Reliabilität von Sprachtests

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    Modeling and verifying the test-retest reliability of the Freiburg monosyllabic speech test in quiet with the Poisson binomial distribution

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    The test-retest reliability of the Freiburg monosyllabic speech test was modeled using different methods. The results were compared to measurements from listeners with and without hearing impairment. The methods are based on the models of Thornton and Raffin as well as Altman et al. Both papers took into account differences in word recognition within the test lists by applying the Poisson binomial distribution and included the variance of the test-list results. The methods allow calculating the bounds of the 90% and 95% confidence intervals when using test lists with 20 words and double lists with 40 words. The data in the current report confirm these bounds. The confidence intervals are broadest for speech recognition scores of 50%. At this score and for test lists with 20 words, the 90% confidence interval has a width of ±20%, corresponding to ±6.0 dB, and the 95% confidence interval has a width of ±25%, corresponding to ±7.4 dB. Thus when evaluating hearing-aid fittings, only differences exceeding this range can be regarded as significantly different.Die Test-Retest-Reliabilität des Freiburger Einsilbertests wurde mit verschiedenen Methoden modelliert und mit Messdaten von Probanden mit und ohne Hörbeeinträchtigung verglichen. Die Methoden bauen auf den Verfahren von Thornton und Raffin sowie Altman et al. auf. Sie berücksichtigen durch die Verwendung der verallgemeinerten Binomialverteilung die Unterschiede im Wortverstehen innerhalb der Testlisten und beinhalten die Varianz der Testlisten. Die Methoden ermöglichen die Bestimmung der Grenzen für die 90%- und 95%-Konfidenzintervalle bei Verwendung von Testlisten mit 20 Wörtern und von Doppellisten mit 40 Wörtern. Diese Grenzen wurden durch die Messdaten bestätigt. Bei einem Sprachverstehen von 50% sind die Konfidenzintervalle am breitesten. Dort hat für Testlisten mit 20 Wörtern das 90%-Konfidenzintervall eine Breite von ±20% bzw. ±6,0 dB und das 95%-Konfidenzintervall eine Breite von ±25% bzw. ±7,4 dB. Für die Hörgeräte-Anpasspraxis bedeutet dies, dass erst Unterschiede, die diese Spanne übersteigen, als signifikant unterschiedlich gewertet werden können
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