Mirman Daniel, McClelland James L, Holt Lori L
Department of Psychology, University of Connecticut, 406 Babbidge Rd., Unit 1020, Storrs, CT 06269-1020, USA.
Psychon Bull Rev. 2006 Dec;13(6):958-65. doi: 10.3758/bf03213909.
We describe an account of lexically guided tuning of speech perception based on interactive processing and Hebbian learning. Interactive feedback provides lexical information to prelexical levels, and Hebbian learning uses that information to retune the mapping from auditory input to prelexical representations of speech. Simulations of an extension of the TRACE model of speech perception are presented that demonstrate the efficacy of this mechanism. Further simulations show that acoustic similarity can account for the patterns of speaker generalization. This account addresses the role of lexical information in guiding both perception and learning with a single set of principles of information propagation.
我们描述了一种基于交互式处理和赫布学习的言语感知词汇引导调谐的解释。交互式反馈将词汇信息提供给词汇前水平,而赫布学习利用该信息重新调整从听觉输入到言语词汇前表征的映射。我们展示了言语感知TRACE模型扩展的模拟,证明了这种机制的有效性。进一步的模拟表明,声学相似性可以解释说话者泛化的模式。这种解释用一套单一的信息传播原则解决了词汇信息在引导感知和学习中的作用。