A framework for testing and comparing binaural models
A framework for testing and comparing binaural models
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DOI：
10.1016/j.heares.2017.11.010
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发表时间：
2018-03-01
期刊：
影响因子：
2.8
通讯作者：
Goodman, Dan P. M.
中科院分区：
文献类型：
--
作者：
Dietz, Mathias;Lestang, Jean-Hugues;Goodman, Dan P. M.
听觉研究有着将实验证据与听觉处理的计算机模拟相结合的丰富历史，以加深我们对声音如何在耳朵和大脑中处理的理论理解。尽管听觉模型在细节和广度上取得了重大进展，但对于听觉通路的许多组成部分，仍然存在不同的模型方法，这些方法通常不等同，而是相互冲突。同样，一些实验研究产生了相互矛盾的结果，导致了争议。这可以通过多个实验数据集和模型方法的系统比较来最好地解决。双耳处理是一个突出的例子，说明了定量理论的发展如何促进我们对现象的理解，但仍然存在几个未解决的问题，其中存在竞争模型方法。本文讨论了一些目前尚未解决或有争议的问题，在双耳建模，以及一些重大的挑战，在比较双耳模型与其他和实验数据。我们引入了一个听觉模型框架，我们相信它可以成为解决当前一些争议的有用基础设施。它在实验中使用的相同范例上操作模型。所提出的框架的核心是一个接口，它连接三个组件，而不管它们的底层编程语言：实验软件，听觉通路模型，和任务相关的决策阶段称为人工观察员，提供相同的输出格式作为测试对象。(C)2017爱思唯尔B.V.保留所有权利。
Auditory research has a rich history of combining experimental evidence with computational simulations of auditory processing in order to deepen our theoretical understanding of how sound is processed in the ears and in the brain. Despite significant progress in the amount of detail and breadth covered by auditory models, for many components of the auditory pathway there are still different model approaches that are often not equivalent but rather in conflict with each other. Similarly, some experimental studies yield conflicting results which has led to controversies. This can be best resolved by a systematic comparison of multiple experimental data sets and model approaches. Binaural processing is a prominent example of how the development of quantitative theories can advance our understanding of the phenomena, but there remain several unresolved questions for which competing model approaches exist. This article discusses a number of current unresolved or disputed issues in binaural modelling, as well as some of the significant challenges in comparing binaural models with each other and with the experimental data. We introduce an auditory model framework, which we believe can become a useful infrastructure for resolving some of the current controversies. It operates models over the same paradigms that are used experimentally. The core of the proposed framework is an interface that connects three components irrespective of their underlying programming language: The experiment software, an auditory pathway model, and task-dependent decision stages called artificial observers that provide the same output format as the test subject. (C) 2017 Elsevier B.V. All rights reserved.