Early Syntactic Bootstrapping in an Incremental Memory-Limited Word Learner

2018-02-08

Proceedings of the AAAI Conference on Artificial Intelligence, 32

Volume

Thirty-Second AAAI Conference on Artificial Intelligence 2018

Main Track: NLP and Knowledge Representation

It has been suggested that early human word learning occurs across learning situations and is bootstrapped by syntactic regularities such as word order. Simulation results from ideal learners and models assuming prior access to structured syn-tactic and semantic representations suggest that it is possible to jointly acquire word order and meanings and that learning is improved as each language capability bootstraps the other.We first present a probabilistic framework for early syntactic bootstrapping in the absence of advanced structured representations, then we use our framework to study the utility of joint acquisition of word order and word referent and its onset, in a memory-limited incremental model. Comparing learning results in the presence and absence of joint acquisition of word order in different ambiguous contexts, improvement in word order results showed an immediate onset, starting in early trials while being affected by context ambiguity. Improvement in word learning results on the other hand, was hindered in early trials where the acquired word order was imperfect,while being facilitated by word order learning in future trials as the acquired word order improved. Furthermore, our results showed that joint acquisition of word order and word referent facilitates one-shot learning of new words as well as inferring intentions of the speaker in ambiguous contexts.

10.1609/aaai.v32i1.11930