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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]

A word's uniqueness point is the earliest point in its spoken form at which the sounds heard so far distinguish it from all competing words in a specified vocabulary. It connects a cohort model of spoken word recognition to the changing size of the lexical cohort.^[ref]

For an invented vocabulary, let three word forms be the phoneme sequences $pata$, $pana$ and $pita$, with spaces ignored and each symbol representing one phoneme. The third word becomes unique after $pi$, while the first two remain ambiguous after $pa$ and diverge at the following consonant. Uniqueness can therefore precede the end of a word.

This is a property of the chosen vocabulary and transcription, not a universal timestamp attached to a spelling. Adding another word beginning $pi$ changes the example. A word that is a complete prefix of another may require an end-of-word cue. Measured reaction time also includes perceptual, decision and motor processes, so it need not equal the lexical uniqueness time.