Paper: Automatic Prosodic Labeling with Conditional Random Fields and Rich Acoustic Features

ACL ID I08-1029
Title Automatic Prosodic Labeling with Conditional Random Fields and Rich Acoustic Features
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

Many acoustic approaches to prosodic la- beling in English have employed only lo- cal classifiers, although text-based classifi- cation has employed some sequential mod- els. In this paper we employ linear chain and factorial conditional random fields (CRFs) in conjunction with rich, contextually-based prosodic features, to exploit sequential de- pendencies and to facilitate integration with lexical features. Integration of lexical and prosodic features improves pitch accent pre- diction over either feature set alone, and for lower accuracy feature sets, factorial CRF models can improve over linear chain based prediction of pitch accent.