"Prosody models based on automatically-derived focus words in narrative text"
Kevyn Collins-Thompson

The goal of this Speech II final project was to increase the appeal
and clarity of voice synthesis for children's stories, without
requiring any human pre-tagging of the text.  To attempt this, I
created very simple models of three 'focus word' types: topic words,
difficult words, and modifier words, which are derived from the story
text based on vocabulary statistics and shallow parsing.  There is
also a time-dependent 'novelty' component.  These models drive
duration and pitch changes in the Festival synthesizer.  For example,
the pitch of topic words is emphasized depending on their relevance
and novelty, and the duration of difficult words can be stretched via
a custom phoneme table.  Future applications of this approach could
include varying the language models used to estimate focus words, so
that the same text could be adapted to different listeners, depending
on their language background and skills.