Multilingual speakers are able to switch from one language to the other (“code-switch”) between or within sentences. Because the underlying cognitive mechanisms are not well understood, we developed a computational cognitive model to shed light on the process of code-switching. We employed the Bilingual Dual-path model, a Recurrent Neural Network of bilingual sentence production (Tsoukala et al., 2017) and simulated sentence production in simultaneous Spanish-English bilinguals. Our first goal was to investigate whether the model would code-switch without being exposed to code-switched training input. The model indeed produced code-switches even without any exposure to such input and patterns of code-switches were in line with earlier linguistic work (Poplack, 2018). Next, we successfully applied the model to investigate possible causes for a specific phenomenon in Spanish-English code-switching: Speakers regularly code-switch in progressive but not in perfect tense structures. To our knowledge, this is the first computational cognitive model that aims to simulate code-switched sentence production.

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