Estimating speaker-specific intonation patterns using the linear alignment model

Modeling speaker-specific intonation is important in several areas, including speaker identification, verification, and imitation using text-to-speech synthesis. However the choice of the intonation model and the estimation of its parameters from spontaneous speech remains a challenge. We propose a way to estimate speaker-specific intonation parameters for a particular superpositional model, the Simplified Linear Alignment Model [1], using robust per-utterance and overall statistics of spontaneous speech. We used this method to compare the intonation of children with autism or language impairment, who often have atypical speech prosody, with that of typically developing children. We found significant differences between the groups, which demonstrates the effectiveness of the proposed method.