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As a sub-discipline of evolutionary and computational linguistics, emergentcommunication (EC) studies communication protocols, called emergent languages,arising in simulations where agents communicate. A key goal of EC is to giverise to languages that share statistical properties with natural languages. Inthis paper, we reinterpret Lewis's signaling game, a frequently used setting inEC, as beta-VAE and reformulate its objective function as ELBO. Consequently,we clarify the existence of prior distributions of emergent languages and showthat the choice of the priors can influence their statistical properties.Specifically, we address the properties of word lengths and segmentation, knownas Zipf's law of abbreviation (ZLA) and Harris's articulation scheme (HAS),respectively. It has been reported that the emergent languages do not followthem when using the conventional objective. We experimentally demonstrate thatby selecting an appropriate prior distribution, more natural segments emerge,while suggesting that the conventional one prevents the languages fromfollowing ZLA and HAS.

Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments