Neural‐network simulation of tonal categorization based on F0 velocity profiles

Perception studies have shown that by the age of six months, infants show particular response patterns to tones in their native language. The present study focuses on how infants might develop lexical tones in Man‐ darin. F0 is generally considered the main cue in tone perception. However, F0 patterns in connected speech display extensive contextual variability. Since speech input to infants consists mainly of multi‐word utterances, tone learning must involve processes that can effectively resolve variability. In this study we explore the Target Approximation model (Xu and Wang, 2001) which characterizes surface F0 as asymptotic movements toward underlying pitch targets defined as simple linear functions. The model predicts that it is possible to infer underlying pitch targets from the manners of F0 movements. Using production data of three of the speakers from Xu (1997), we trained a self‐organizing neural network with both F0 profiles and F0 velocity profiles as input. In the testing phase, velocity pro...