The rise/fall/connection model of intonation
Speech Communication
Unsupervised and semi-supervised learning of tone and pitch accent
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Detecting pitch accents at the word, syllable and vowel level
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Affirmative cue words in task-oriented dialogue
Computational Linguistics
Analysis of inter-transcriber consistency in the Cat_ToBI prosodic labeling system
Speech Communication
A fuzzy classifier to deal with similarity between labels on automatic prosodic labeling
Computer Speech and Language
| Hi-index | 0.00 |
We present Quantized Contour Modeling (QCM), a Bayesian approach to the classification of acoustic contours. We evaluate the performance of this technique in the classification of prosodic events. We find that, on BURNC, this technique can successfully classify pitch accents with 63.99% accuracy (.4481 CER), and phrase ending tones with 72.91% accuracy.