 Cohort model

A cohort model explains spoken word recognition through an evolving set of candidate words, the lexical cohort. An initial stretch of speech activates plausible candidates; later acoustic evidence and, depending on the model version, contextual information constrain recognition. William D. Marslen-Wilson and Alan Welsh's 1978 study connected this account with experimental manipulations of continuous speech.^[ref]

For an illustrative English vocabulary, the opening sounds of “candle”, “candy” and “canister” initially overlap. Hearing the next consonant can remove “canister” while leaving the other two plausible; later sounds separate them. The candidates depend on pronunciation and the listener's vocabulary, not merely on matching written letters.

A deliberately simplified noise-free rule isHere $C_t$ is the candidate set after the evidence available at step $t$. This filtering illustration is not a fitted psychological model: noisy speech, graded activation and recovery from misleading evidence require additional assumptions. A uniqueness point concerns when the remaining acoustic prefix distinguishes a word within a specified vocabulary; it need not coincide with the listener's measured response time.

The original task comparisons motivate testing a model on intermediate behaviour and contextual effects, not just final accuracy.^[ref]