University of Geneva, Geneva Emotion Research Group.
University of Pennsylvania, Department of Psychology.
J Exp Psychol Hum Percept Perform. 2009 Dec;35(6):1913-1933. doi: 10.1037/a0015781.
Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is more difficult but tractable under specific task conditions. In 2 experiments, adult participants learned either a unidimensional or a multidimensional category distinction with or without supervision (feedback) during learning. The unidimensional distinctions were readily learned and supervision proved beneficial, especially in maintaining category learning beyond the learning phase. Learning the multidimensional category distinction proved to be much more difficult and supervision was not nearly as beneficial as with unidimensionally defined categories. Maintaining a learned multidimensional category distinction was only possible when the distributional information that identified the categories remained present throughout the testing phase. We conclude that listeners are sensitive to both trial-by-trial feedback and the distributional information in the stimuli. Even given limited exposure, listeners learned to use 2 relevant dimensions, albeit with considerable difficulty.
学习识别特定语言的音位系统的对比可以被视为在多维心理物理空间中形成类别。关于分布定义的视觉类别学习的研究表明，定义在一维上的类别很容易学习，而学习多维类别则更困难，但在特定任务条件下是可行的。在 2 项实验中，成年参与者在学习过程中接受或不接受监督（反馈），学习一维或多维类别区分。一维区分很容易学习，监督证明是有益的，特别是在学习阶段之后维持类别学习方面。学习多维类别区分证明要困难得多，监督的效果远不如一维定义的类别。只有当在测试阶段始终存在标识类别的分布信息时，才能维持已学习的多维类别区分。我们的结论是，听众对逐次试验的反馈和刺激中的分布信息都很敏感。即使在有限的接触下，听众也学会了使用 2 个相关维度，尽管存在相当大的困难。
