Ten Bosch Louis, Boves Lou, Ernestus Mirjam
Center for Language Studies, Radboud University, 6525 HT Nijmegen, The Netherlands.
Brain Sci. 2022 May 23;12(5):681. doi: 10.3390/brainsci12050681.
This article presents DIANA, a new, process-oriented model of human auditory word recognition, which takes as its input the acoustic signal and can produce as its output word identifications and lexicality decisions, as well as reaction times. This makes it possible to compare its output with human listeners' behavior in psycholinguistic experiments. DIANA differs from existing models in that it takes more available neuro-physiological evidence on speech processing into account. For instance, DIANA accounts for the effect of ambiguity in the acoustic signal on reaction times following the Hick-Hyman law and it interprets the acoustic signal in the form of spectro-temporal receptive fields, which are attested in the human superior temporal gyrus, instead of in the form of abstract phonological units. The model consists of three components: activation, decision and execution. The activation and decision components are described in detail, both at the conceptual level (in the running text) and at the computational level (in the Appendices). While the activation component is independent of the listener's task, the functioning of the decision component depends on this task. The article also describes how DIANA could be improved in the future in order to even better resemble the behavior of human listeners.
本文介绍了DIANA,这是一种全新的、面向过程的人类听觉单词识别模型,它将声学信号作为输入,并能输出单词识别结果、词汇判断以及反应时间。这使得在心理语言学实验中,能够将其输出结果与人类听众的行为进行比较。DIANA与现有模型的不同之处在于,它考虑了更多关于语音处理的神经生理学证据。例如,DIANA依据希克-海曼定律,解释了声学信号中的模糊性对反应时间的影响,并且它以频谱-时间感受野的形式来解释声学信号,这种形式已在人类颞上回中得到证实,而不是以抽象的语音单位形式。该模型由三个部分组成:激活、决策和执行。文章在概念层面(正文部分)和计算层面(附录部分)详细描述了激活和决策部分。虽然激活部分独立于听众的任务,但决策部分的功能则取决于该任务。本文还描述了未来如何改进DIANA,以便更接近人类听众的行为。