Publications

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

Abstract

We propose that word recognition in continuous speech is subject to constraints on what may constitute a viable word of the language. This Possible-Word Constraint (PWC) reduces activation of candidate words if their recognition would imply word status for adjacent input which could not be a word - for instance, a single consonant. In two word-spotting experiments, listeners found it much harder to detectapple,for example, infapple(where [f] alone would be an impossible word), than invuffapple(wherevuffcould be a word of English). We demonstrate that the PWC can readily be implemented in a competition-based model of continuous speech recognition, as a constraint on the process of competition between candidate words; where a stretch of speech between a candidate word and a (known or likely) word boundary is not a possible word, activation of the candidate word is reduced. This implementation accurately simulates both the present results and data from a range of earlier studies of speech segmentation.

Abstract

Finnish vowel harmony rules require that if the vowel in the first syllable of a word belongs to one of two vowel sets, then all subsequent vowels in that word must belong either to the same set or to a neutral set. A harmony mismatch between two syllables containing vowels from the opposing sets thus signals a likely word boundary. We report five experiments showing that Finnish listeners can exploit this information in an on-line speech segmentation task. Listeners found it easier to detect words likehymyat the end of the nonsense stringpuhymy(where there is a harmony mismatch between the first two syllables) than in the stringpyhymy(where there is no mismatch). There was no such effect, however, when the target words appeared at the beginning of the nonsense string (e.g.,hymypuvshymypy). Stronger harmony effects were found for targets containing front harmony vowels (e.g.,hymy) than for targets containing back harmony vowels (e.g.,paloinkypaloandkupalo). The same pattern of results appeared whether target position within the string was predictable or unpredictable. Harmony mismatch thus appears to provide a useful segmentation cue for the detection of word onsets in Finnish speech.