Functional data analyses of lip motion.
The vocal tract's motion during speech is a complex patterning of the movement of many different articulators according to many different time functions. Understanding this myriad of gestures is important to a number of different disciplines including automatic speech recognition, speech and language pathologies, speech motor control, and experimental phonetics. Central issues are the accurate description of the shape of the vocal tract and determining how each articulator contributes to this shape. A problem facing all of these research areas is how to cope with the multivariate data from speech production experiments. In this paper techniques are described that provide useful tools for describing multivariate functional data such as the measurement of speech movements. The choice of data analysis procedures has been motivated by the need to partition the articulator movement in various ways: end effects separated from shape effects, partitioning of syllable effects, and the splitting of variation within an articulator site from variation from between sites. The techniques of functional data analysis seem admirably suited to the analyses of phenomena such as these. Familiar multivariate procedures such as analysis of variance and principal components analysis have their functional counterparts, and these reveal in a way more suited to the data the important sources of variation in lip motion. Finally, it is found that the analyses of acceleration were especially helpful in suggesting possible control mechanisms. The focus is on using these speech production data to understand the basic principles of coordination. However, it is believed that the tools will have a more general use.
Ramsay
J O
JO
McGill University, Montreal, Quebec, Canada. ramsay@psych.mcgill.ca
Munhall
K G
KG
Gracco
V L
VL
Ostry
D J
DJ
D006801:Humans; D008046:Lip / Q000502:physiology*; D008297:Male; D008962:Models, Theoretical; D009038:Motion; D009622:Noise; D013060:Speech; D013061:Speech Acoustics; D013068:Speech Production Measurement