Paper: Exploiting Acoustic and Syntactic Features for Prosody Labeling in a Maximum Entropy Framework

ACL ID N07-1001
Title Exploiting Acoustic and Syntactic Features for Prosody Labeling in a Maximum Entropy Framework
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

In this paper we describe an automatic prosody labeling framework that exploits both language and speech information. We model the syntactic-prosodic informa- tion with a maximum entropy model that achieves an accuracy of 85.2% and 91.5% for pitch accent and boundary tone la- beling on the Boston University Radio News corpus. We model the acoustic- prosodic stream with two different mod- els, one a maximum entropy model and the other a traditional HMM. We finally couple the syntactic-prosodic and acoustic- prosodic components to achieve signifi- cantly improved pitch accent and bound- ary tone classification accuracies of 86.0% and 93.1% respectively. Similar experimen- tal results are also reported on Boston Di- rections corpus.