Auditory model-based parameter estimation and selection of the most informative experimental conditions
Identifying the causes underlying a person’s hearing impairment is challenging. It requires linking the results of listening tests to possible pathologies of the highly non-linear auditory system. This process is further aggravated by restrictions in measurement time, especially in clinical settings...
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Published in | Acta acustica Vol. 8; p. 3 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Stuttgart
EDP Sciences
2024
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ISSN | 2681-4617 1610-1928 2681-4617 1861-9959 |
DOI | 10.1051/aacus/2023064 |
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Abstract | Identifying the causes underlying a person’s hearing impairment is challenging. It requires linking the results of listening tests to possible pathologies of the highly non-linear auditory system. This process is further aggravated by restrictions in measurement time, especially in clinical settings. A central but difficult goal is thus, to maximize the diagnostic information that is collectable within a given time frame. This study demonstrates the practical applicability of the model-based experiment-steering procedure introduced in Herrmann and Dietz (2021, Acta Acustica, 5:51). The approach chooses the stimuli that are presented and estimates the model parameters best predicting the subject’s performance using a maximum-likelihood method. The same binaural tone-in-noise detection task was conducted using two measurement procedures: A standard adaptive staircase procedure and the model-based selection procedure based on an existing model. The model-steered procedure reached the same accuracy of model parameter estimation in on average only 42% of the time that was required with the standard adaptive procedure. Difficulties regarding the choice of a reliable model and reasonable discretization steps of its parameters are discussed. Although the physiological causes of an individual’s results cannot directly be inferred using this procedure, a characterization in terms of functional parameters is possible. |
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AbstractList | Identifying the causes underlying a person’s hearing impairment is challenging. It requires linking the results of listening tests to possible pathologies of the highly non-linear auditory system. This process is further aggravated by restrictions in measurement time, especially in clinical settings. A central but difficult goal is thus, to maximize the diagnostic information that is collectable within a given time frame. This study demonstrates the practical applicability of the model-based experiment-steering procedure introduced in Herrmann and Dietz (2021, Acta Acustica, 5:51). The approach chooses the stimuli that are presented and estimates the model parameters best predicting the subject’s performance using a maximum-likelihood method. The same binaural tone-in-noise detection task was conducted using two measurement procedures: A standard adaptive staircase procedure and the model-based selection procedure based on an existing model. The model-steered procedure reached the same accuracy of model parameter estimation in on average only 42% of the time that was required with the standard adaptive procedure. Difficulties regarding the choice of a reliable model and reasonable discretization steps of its parameters are discussed. Although the physiological causes of an individual’s results cannot directly be inferred using this procedure, a characterization in terms of functional parameters is possible. |
Author | Dietz, Mathias Encke, Jörg Dietze, Anna Reinsch, Anna-Lena |
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SubjectTerms | Accuracy audiological diagnostics binaural hearing computational audiology Data collection Experiments Mathematical models Measurement techniques Model accuracy model-based experiment steering Parameter estimation Parameter identification Pathology Performance prediction Physiology Steering Time measurement tone-in-noise detection |
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Title | Auditory model-based parameter estimation and selection of the most informative experimental conditions |
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