Publications

Abstract

The present experiment tested the suggestion that human listeners may exploit durational information in speech to parse continuous utterances into words. Listeners were presented with six-syllable unpredictable utterances under noise-masking, and were required to judge between alternative word strings as to which best matched the rhythm of the masked utterances. For each utterance there were four alternative strings: (a) an exact rhythmic and word boundary match, (b) a rhythmic mismatch, and (c) two utterances with the same rhythm as the masked utterance, but different word boundary locations. Listeners were clearly able to perceive the rhythm of the masked utterances: The rhythmic mismatch was chosen significantly less often than any other alternative. Within the three rhythmically matched alternatives, the exact match was chosen significantly more often than either word boundary mismatch. Thus, listeners both perceived speech rhythm and used durational cues effectively to locate the position of word boundaries.

Abstract

An introductory study of the perception of stochastically specified events is reported. The initial problem was to determine whether the perceiver can split visual input data of this kind into random and determined components. The inability of subjects to do so with the stimulus material used (a filmlike sequence of dot patterns), led to the more general question of how subjects code this kind of visual material. To meet the difficulty of defining the subjects' responses, two experiments were designed. In both, patterns were presented as a rapid sequence of dots on a screen. The patterns were more or less disturbed by “noise,” i.e. the dots did not appear exactly at their proper places. In the first experiment the response was a rating on a semantic scale, in the second an identification from among a set of alternative patterns. The results of these experiments give some insight in the coding systems adopted by the subjects. First, noise appears to be detrimental to pattern recognition, especially to patterns with little spread. Second, this shows connections with the factors obtained from analysis of the semantic ratings, e.g. easily disturbed patterns show a large drop in the semantic regularity factor, when only a little noise is added.