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Title: Methods for PoLaR Explorations with Machine Learning: Grammatical Analysis of Intonation without Grammatical Labels
This study provides a proof-of-concept for a new method for analyzing intonational form and meaning, demonstrated by analysis of mirative utterances in American English. Here, K-means clustering using measures derived from PoLaR labels (i.e., TCoG) revealed emergent clusters of pitch accents that are suggestive of familiar phonological categories (e.g., MAE_ToBI L+H*). A Random Forest analysis then classified utterance-level meaning based on measures from both smaller granularity (related to individual pitch accents) and larger granularity (related to utterance level meaning), showing >85% correct categorization of exclamative vs filler sentences. This work has implications for how to model mappings between prosody and meaning, especially where existing phonological categories alone don’t identify semantic/pragmatic categories.  more » « less
Award ID(s):
2042702
PAR ID:
10436610
Author(s) / Creator(s):
Date Published:
Journal Name:
International Congress of Phonetic Sciences
ISSN:
2412-0669
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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