Listeners Exploit Syntactic Structure On-Line to Restrict Their Lexical Search to a Subclass of Verbs

Many experiments have shown that listeners actively build expectations about up-coming words, rather than simply waiting for information to accumulate. The online construction of a syntactic structure is one of the cues that listeners may use to construct strong expectations about the possible words they will be exposed to. For example, speakers of verb-final languages use pre-verbal arguments to predict on-line the kind of arguments that are likely to occur next (e.g., Kamide, 2008, for a review). Although in SVO languages information about a verb's arguments typically follows the verb, some languages use pre-verbal object pronouns, potentially allowing listeners to build on-line expectations about the nature of the upcoming verb. For instance, if a pre-verbal direct object pronoun is heard, then the following verb has to be able to enter a transitive structure, thus excluding intransitive verbs. To test this, we used French, in which object pronouns have to appear pre-verbally, to investigate whether listeners use this cue to predict the occurrence of a transitive verb. In a word detection task, we measured the number of false alarms to sentences that contained a transitive verb whose first syllable was homophonous to the target monosyllabic verb (e.g., target "dort" /dɔʁ/ to sleep and false alarm verb "dorlote" /dɔʁlɔt/ to cuddle). The crucial comparison involved two sentence types, one without a pre-verbal object clitic, for which an intransitive verb was temporarily a plausible option (e.g., "Il dorlote" / He cuddles) and the other with a pre-verbal object clitic, that made the appearance of an intransitive verb impossible ("Il le dorlote" / He cuddles it). Results showed a lower rate of false alarms for sentences with a pre-verbal object pronoun (3%) compared to locally ambiguous sentences (about 20%). Participants rapidly incorporate information about a verb's argument structure to constrain lexical access to verbs that match the expected subcategorization frame.