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Two computational analyses of phoneme transitions are presented for American English. A strong bimodal distribution was found such that any given phoneme pair is expected to occur either only across a word boundary or only within a word. This is a type of regularity that language learners have been shown to be particularly adept at detecting. This result indicates that highly accurate word segmentation of American English speech is possible by a system that attends only to the statistics of single phoneme transitions.
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Stored only when both papers are in the corpus — 39 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.