A model of speech segmentation in a stress language is proposed, according to which the occurrence of a strong syllable triggers segmentation of the speech signal, whereas occurrence of a weak syllable does not trigger segmentation. We report experiments in which listeners detected words embedded in nonsense bisyllables more slowly when the bisyllable had two strong syllables than when it had a strong and a weak syllable; mint was detected more slowly in mintayve than in mintesh. According to our proposed model, this result is an effect of segmentation: When the second syllable is strong, it is segmented from the first syllable, and successful detection of the embedded word therefore requires assembly of speech material across a segmentation position. Speech recognition models involving phonemic or syllabic recoding, or based on strictly left-to-right processes, do not predict this result. It is argued that segmentation at strong syllables in continuous speech recognition serves the purpose of detecting the most efficient locations at which to initiate lexical access. (C) 1988 by the American Psychological Association