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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 lexical cohort is a set of candidate words compatible with an initial stretch of speech during spoken word recognition. In a cohort model, new acoustic information changes which candidates remain plausible. The term describes candidates in recognition, rather than a group of people followed in a longitudinal study.^[ref]

For an English example, an initial “cap” can fit “captain”, “captive” and “capsule”; later sounds distinguish them. The example assumes a particular vocabulary and pronunciation: spelling alone does not specify an acoustic cohort.

The 1978 experiments compared repeating ongoing speech with detecting altered pronunciations while following a written passage. Effects of where a mispronunciation occurred, and differences in the influence of context across tasks, constrained accounts of how incoming speech and prior expectations interact.^[ref] A candidate set is a model construct; behaviour supplies evidence about its time course rather than a literal inventory of consciously considered words.

Spoken word recognition is the process of identifying familiar spoken forms from an unfolding speech signal and accessing the corresponding lexemes. It occurs as information arrives: the beginning of an utterance may fit several possible forms, while later sounds distinguish them. The temporary candidate set is a lexical cohort.

For example, the beginning of “candle” is also compatible with “candy”. As the later sounds arrive, the evidence changes. Recognizing the item therefore involves both sensitivity to the incoming sounds and access to stored phonological representations; it is not necessary to wait for a silent gap before beginning to interpret the signal.

A 2005 mouse tracking experiment made this changing evidence visible in action. Participants heard a target name while moving toward one of two pictures. A similar-sounding alternative altered the movement path even on trials ending at the correct picture. The result supported an account in which spoken word recognition can influence an ongoing action before the final choice is complete.^[ref]

The measured cursor path is a behavioural consequence of recognition, rather than a direct recording of a phonological representation. The inference linking the two must be made explicit.

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.

William D. Marslen-Wilson investigated the time course of spoken word recognition. Work with Alan Welsh helped develop the cohort model: early sounds make several words plausible, and subsequent evidence constrains that lexical cohort.^[ref]

Their experiments manipulated pronunciation within continuous speech rather than presenting only isolated written words. This made the timing of incoming information part of the question. A model can explain a listener's eventual correct answer yet still fail to explain how context and partial speech influence the response while the word unfolds.^[ref]