Chinese Accent Detection Using Acoustic Feature Sets with Context Features

DOI

10.2991/lemcs-14.2014.228How to use a DOI?

Keywords

Chinese accent detection; acoustic features; context features; NaiveBayes classifier;accent detection

Abstract

Accent is a critically important component of spoken communication. In this paper, we use acoustic features with context features to detect Chinese accent, and use NaiveBayes classifier to conduct model based on ASCCD reading discourse corpus. For comparison purposes, we digitally added white noise to ASCCD, and regarded it as ASCCD (white). NaiveBayes classifier is utilized to model the acoustic feature sets, which adequately present the property of the current syllable and context. The experimental results indicate that the acoustic feature sets with context features achieve 80.7% accent detection accuracy on ASCCD. The experiment also demonstrate that the acoustic feature sets with context features achieve 75.7% accent detection accuracy on ASCCD(white). Across these acoustic feature sets, we find pitch features to be the most predictive of Chinese accent on ASCCD and on ASCCD (white).Context is important to Chinese accent detection on ASCCD and on ASCCD (white).And the experimental results show that the NaiveBayes classification has a good classification result for these.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yunxue Zhao
AU  - Long Zhang
AU  - Shijie Zheng
PY  - 2014/05
DA  - 2014/05
TI  - Chinese Accent Detection Using Acoustic Feature Sets with Context Features
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 1017
EP  - 1020
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.228
DO  - 10.2991/lemcs-14.2014.228
ID  - Zhao2014/05
ER  -