Year: 2004
Type: conference-paper
Abstract: Prosody has been traditionally regarded as useless for word recognition.In this paper, we provide a schematic view describing how prosody can help word recognition.We provide our view in terms of a Bayesian network that models the stochastic dependence among acoustic observation, word, prosody, syntax and meaning, and an information-theoretic analysis proving that the mutual information between acoustic observation and correct word hypotheses improves if prosody is jointly modeled with word in a prosody dependent speech recognition framework.We also report our experiment on Radio News Corpus in which prosody has improved word recognition accuracy by 2.5%.
Source: Speech prosody
Authors: Ken Chen, Mark Hasegawa-Johnson
Institution: University of Illinois Urbana-Champaign
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W116380143