Accurate modeling of co-articulation, the context-sensitive merging of the boundaries between allophones in continuous speech, is vital for natural sounding speech synthesis. This paper describes initial research investigating the use of Bézier Curves to form models of co-articulation in human speech. A 12th order, pitch synchronous line spectral pair (LSP) analysis is performed on a corpus of 239 phonetically balanced sentences of English speech. The resulting data are divided to form an inventory of the diphones occurring in the speech database. The trajectory of each line spectral pair parameter through each diphone can then be represented by a single cubic Bézier curve segment, found using the Levenberg-Marquardt curve fitting method. Results are presented showing the accuracy of Bézier models of the co-articulation between different types of speech sounds.
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