RESUMO
There is a significant body of research examining the intelligibility of sinusoidal replicas of natural speech. Discussion has followed about what the sinewave speech phenomenon might imply about the mechanisms underlying phonetic recognition. However, most of this work has been conducted using sentence material, making it unclear what the contributions are of listeners' use of linguistic constraints versus lower level phonetic mechanisms. This study was designed to measure vowel intelligibility using sinusoidal replicas of naturally spoken vowels. The sinusoidal signals were modeled after 300 /hVd/ syllables spoken by men, women, and children. Students enrolled in an introductory phonetics course served as listeners. Recognition rates for the sinusoidal vowels averaged 55%, which is much lower than the â¼95% intelligibility of the original signals. Attempts to improve performance using three different training methods met with modest success, with post-training recognition rates rising by â¼5-11 percentage points. Follow-up work showed that more extensive training produced further improvements, with performance leveling off at â¼73%-74%. Finally, modeling work showed that a fairly simple pattern-matching algorithm trained on naturally spoken vowels classified sinewave vowels with 78.3% accuracy, showing that the sinewave speech phenomenon does not necessarily rule out template matching as a mechanism underlying phonetic recognition.