抄録
Offer Organization: Japan Society for the Promotion of Science, System Name: Grants-in-Aid for Scientific Research, Category: Grant-in-Aid for Scientific Research (C), Fund Type: -, Overall Grant Amount: - (direct: 1300000, indirect: -)
This research demonstrates syntactic effects in resolving lexical ambiguity in Japanese, an S-O-V language. In particular, the effect of a postpositional particle on the semantic access of sentence-final ambiguous verbs in two kinds of sentences, (a) S-ga-V sentences (subject, subjective postpositional particle, and ambiguous verb) and (b) O-wo-V sentences (object, objective postpositional particle, and ambiguous verb), will be demonstrated. In this research, The postpositional particles are designed to disambiguate the verbs' meanings as (a) S-ga-Vi. (intransitive verb) or (b) O-wo-Vt. (transitive verb).
A cross-modal priming method was used in which a target noun was visually presented by Kanji characters one-syllable before the end, or immediately after the end, of a sentence-final verb presented auditorily. One target noun was related to both the prime verb's meaning and the postpositional particle used (context-dependent), while another target noun was related to only the prime verb's meaning, but it was unrelated to the postpositional particle used (context-independent), and a third target was unrelated to both of the verb's and the particle's meaning. For this analysis, we hand coded the data of naming latencies based on digital spectrograms of subjects' voices, because the voice key measure has been considered unsuitable to measure naming latency accurately.
This research has been pursued with reference to the constraint-based lexicalist approach. The parallel distributed processing (PDP) models (connectionist models) of disambiguation are well suited to implement this constraint-based lexicalist view that human natural language understanding involves constraint-satisfaction mechanisms. We performed a computer simulation of this experiment using our PDP model. Consistent with experimental data, the PDP model can successfully simulate the effect of context-dependent and context-independent frequencies of ambiguous verbs in the time-course of activation.