Indian Accent Detection using Dynamic Time Warping

被引：0

作者：

Joseph, Jerin ^{[1
]}

Upadhya, Savitha S. ^{[1
]}

机构：

[1] FrCRIT Mumbai, Elect & Telecommun Dept, Mumbai, Maharashtra, India

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON POWER, CONTROL, SIGNALS AND INSTRUMENTATION ENGINEERING (ICPCSI) | 2017年

关键词：

Voice Onset Time; Teager Energy Operator; Dynamic Time Warping;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This investigation aims at designing an accent detection system by recognizing various accents as an input. It aims to identify the accent of a person from his or her voice. The different accents that are detected by the system are the native Indian accents like Bengali, Gujarati, Malayalam and Marathi. The features used for detecting the accents are Voice Onset Time (VOT) and Mel Frequency Cepstral Coefficients (MFCC). These features were extracted for the spoken words having unvoiced stops \p\, V\ and \k\. Teager Energy Operator (TEO), which is a non linear energy tracking signal operator, is used for detecting the VOT. Thirteen MFCC features are extracted in the conventional way. The classifier used to detect the accented speech is Dynamic Time Warping (DTW) algorithm.

引用

页码：2814 / 2817

页数：4

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