A Multi-Dialectal, Longitudinal Corpus of Human-AI Hybrid Language Production

Abstract

This paper presents a multi-dialectal, longitudinal corpus of human-AI hybrid language production, comprising purely human-written texts, purely LLM-generated texts, and hybrid texts produced under different LLM-assistance modes (e.g., stylistic suggestions, short continuations, partial essay generation). The corpus includes 693 participants from five national English dialects, with natural and hybrid samples paired within individuals over a four-week period. This design enables investigation of both short- and longer-term effects of LLM assistance on language use across geographic and social contexts. To illustrate the corpus’s utility, we analyze linguistic features across three dimensions: lexical diversity, syntactic complexity, and stylistic variation. The results show that LLM assistance enhances lexical diversity without a corresponding increase in syntactic complexity, revealing distinct effects across linguistic dimensions. Overall, this corpus offers a valuable resource for studying human-AI interaction, dialectal variation, and the influence of AI assistance on written language.

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