Hierarchical structure and word strength prediction of Mandarin prosody

Journal article

We use Stem-ML to build an automatic learning system for Mandarin prosody that allows us to make quantitative measurements for prosodic strengths. Stem-ML is a phenomenological model of the muscle dynamics and planning process that controls the tension of the vocal folds. Because Stem-ML describes the interactions between nearby tones and accents, we were able to use a highly constrained model with only one accent template for each lexical tone category, and a single prosodic strength per word. The model accurately reproduces the intonation of the speaker, capturing 87% of the variance of the speech's fundamental frequency, f0. The result reveals strong alternating metrical patterns in words, and suggests that the speaker uses word strength to mark a hierarchy of sentence, clause, phrase, and word boundaries.

Authors: Kochanski, G; Shih, C; Jing, H

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: International Journal of Speech Technology
• Volume: 6
• Issue: 1
• Pages: 33-43
• Publication date: 2003-01-01
• DOI: 10.1023/A:1021095805490
• EISSN: 1572-8110
• ISSN: 1381-2416
• Language: English
• Keywords: modeling; Mandarin Chinese; dynamics; tone; intonation; prosody
• Subjects: Linguistics