Information theory has shown that exponential distributions are beneficial to the design of efficient communication systems, because they are both optimal for coding purposes and memoryless. It has recently been shown that Sinosphere family names are exponentially distributed, and this talk will show how, consistent with this, the empirical distributions of names -- and other lexical items -- that English speakers and hearers engage with in moment to moment communication are also exponential, such that the Zipfian distributions long thought to play a functional role in language an artifact of the mixing of these empirical distributions. This talk will illustrate the detailed workings of the communicative process that this distributional structure supports by presenting a full account of the incremental, discriminative syntactic and semantic properties of personal names. It will also show that the distributional structures supporting this process are universal to the world’s major languages, and that the empirical distributions of English nouns and verbs also share this structure. Finally it will lay out the implications that the phenomena identified here have for theoretical understandings of human communication, and cognition more generally.

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