@inproceedings{zhang-2019-data,
title = "Data mining {M}andarin tone contour shapes",
author = "Zhang, Shuo",
booktitle = "Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4217",
doi = "10.18653/v1/W19-4217",
pages = "144--153",
abstract = "In spontaneous speech, Mandarin tones that belong to the same tone category may exhibit many different contour shapes. We explore the use of time-series data mining techniques for understanding the variability of tones in a large corpus of Mandarin newscast speech. First, we adapt a graph-based approach to characterize the clusters (fuzzy types) of tone contour shapes observed in each tone n-gram category. Second, we show correlations between these realized contour shape clusters and a bag of automatically extracted linguistic features. We discuss the implications of the current study within the context of phonological and information theory.",
}
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<abstract>In spontaneous speech, Mandarin tones that belong to the same tone category may exhibit many different contour shapes. We explore the use of time-series data mining techniques for understanding the variability of tones in a large corpus of Mandarin newscast speech. First, we adapt a graph-based approach to characterize the clusters (fuzzy types) of tone contour shapes observed in each tone n-gram category. Second, we show correlations between these realized contour shape clusters and a bag of automatically extracted linguistic features. We discuss the implications of the current study within the context of phonological and information theory.</abstract>
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%0 Conference Proceedings
%T Data mining Mandarin tone contour shapes
%A Zhang, Shuo
%S Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology
%D 2019
%8 aug
%I Association for Computational Linguistics
%C Florence, Italy
%F zhang-2019-data
%X In spontaneous speech, Mandarin tones that belong to the same tone category may exhibit many different contour shapes. We explore the use of time-series data mining techniques for understanding the variability of tones in a large corpus of Mandarin newscast speech. First, we adapt a graph-based approach to characterize the clusters (fuzzy types) of tone contour shapes observed in each tone n-gram category. Second, we show correlations between these realized contour shape clusters and a bag of automatically extracted linguistic features. We discuss the implications of the current study within the context of phonological and information theory.
%R 10.18653/v1/W19-4217
%U https://aclanthology.org/W19-4217
%U https://doi.org/10.18653/v1/W19-4217
%P 144-153
Markdown (Informal)
[Data mining Mandarin tone contour shapes](https://aclanthology.org/W19-4217) (Zhang, 2019)
ACL
- Shuo Zhang. 2019. Data mining Mandarin tone contour shapes. In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 144–153, Florence, Italy. Association for Computational Linguistics.