Across multiple situations, child and adult learners are sensitive to co-occurrences between individual words and their referents in the environment, which provide a means by which the ambiguity of word-world mappings may be resolved (Monaghan & Mattock, 2012; Scott & Fisher, 2012; Smith & Yu, 2008; Yu & Smith, 2007). In three studies, we tested whether cross-situational learning is sufficiently powerful to support simultaneous learning the referents for words from multiple grammatical categories, a more realistic reflection of more complex natural language learning situations. In Experiment 1, adult learners heard sentences comprising nouns, verbs, adjectives, and grammatical markers indicating subject and object roles, and viewed a dynamic scene to which the sentence referred. In Experiments 2 and 3, we further increased the uncertainty of the referents by presenting two scenes alongside each sentence. In all studies, we found that cross-situational statistical learning was sufficiently powerful to facilitate acquisition of both vocabulary and grammar from complex sentence-to-scene correspondences, simulating the situations that more closely resemble the challenge facing the language learner.

在多种情况下，儿童和成人学习者对环境中单个单词及其所指对象的共现很敏感，这为解决单词世界映射的歧义提供了一种方法（Monaghan＆Mattock，2012； Scott＆Fisher） ，2012; Smith＆Yu，2008; Yu＆Smith，2007）。在三项研究中，我们测试了跨情境学习是否足够强大以支持同时学习多个语法类别中的单词的指称对象，这是对更复杂的自然语言学习情况的更现实反映。在实验1中，成年学习者听到了由名词，动词，形容词和指示主语和宾语角色的语法标记组成的句子，并查看了该句子所引用的动态场景。在实验2和3中，通过在每个句子旁边显示两个场景，我们进一步增加了被指对象的不确定性。在所有研究中，我们发现跨情境的统计学习功能强大到足以促进从复杂的句子到场景的对应关系中词汇和语法的获取，模拟了与语言学习者所面临挑战更相似的情况。