Publications

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.

Abstract

This paper presents lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.