Automatized phonological vocabulary knowledge as L2 cognitive fluency: Testing the declarative–automatized integrative model in L2 speech production

Prior studies developed a lexicosemantic judgment task (LJT) to assess automatized phonological vocabulary knowledge, which reflects the accurate, prompt, and stable access to L2 phonological vocabulary knowledge in contexts. Automatized vocabulary knowledge has been shown to strongly predict general listening ability. Shifting the focus on automaticity in speech production, the current study explored the role of automatized vocabulary knowledge as a measure of L2 cognitive fluency predicting L2 utterance fluency (UF) in spontaneous speech. A total of 210 university students took a multiple-choice vocabulary test and the LJT to assess the declarative and automatized aspects of phonological vocabulary knowledge, respectively. UF was measured as articulation rate and mid/end-clause silent pause ratio, elicited through picture narrative and personal opinion tasks, each presenting differential lexical demands. Memory-based cognitive aptitude was also considered. Mixed-effects regression analyses revealed that automatized vocabulary knowledge, rather than the declarative counterpart, underlies fluent speech performance free of undue pauses. Task effects were identified, indicating that automatized vocabulary knowledge is sensitive to the lexical demands of speech tasks.