Non-native speakers show difficulties with spoken word processing. Many
studies attribute these difficulties to imprecise phonological encoding of
words in the lexical memory. We test an alternative hypothesis: that some of
these difficulties can arise from the non-native speakers' phonetic perception.
We train a computational model of phonetic learning, which has no access to
phonology, on either one or two languages. We first show that the model
exhibits predictable behaviors on phone-level and word-level discrimination
tasks. We then test the model on a spoken word processing task, showing that
phonology may not be necessary to explain some of the word processing effects
observed in non-native speakers. We run an additional analysis of the model's
lexical representation space, showing that the two training languages are not
fully separated in that space, similarly to the languages of a bilingual human
speaker.

研究发现，非母语人士在处理口语时存在困难，导致其在词汇记忆的语音编码上不够准确，本研究使用计算模型模拟语音学习，发现有些非母语人士的口音知觉可能是导致这种困难的原因之一。