The nature of English diphthongs has been much disputed. By
now, the most influential account argues that diphthongs are
phoneme entities rather than vowel combinations. However,
mixed results have been reported regarding whether the rate of
formant transition is the most reliable attribute in the perception
and production of diphthongs. Here, we used computational
modelling to explore the underlying forms of diphthongs. We
tested the assumption that diphthongs have dynamic
articulatory targets by training an articulatory synthesiser with
a three-dimensional (3D) vocal tract model to learn English
words. An automatic phoneme recogniser was constructed to
guide the learning of the diphthongs. Listening experiments by
native listeners indicated that the model succeeded in learning
highly intelligible diphthongs, providing support for the
dynamic target assumption. The modelling approach paves a
new way for validating hypotheses of speech perception and
production
