Accent Recognition System Using Deep Belief Networks for Telugu Speech Signals

被引：2

作者：

Mannepalli, Kasiprasad ^{[1
]}

Sastry, Panyam Narahari ^{[2
]}

Suman, Maloji ^{[1
]}

机构：

[1] KL Univ, KLEF, Guntur, AP, India

[2] CBIT, Hyderabad, Telangana, India

来源：

PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, FICTA 2016, VOL 1 | 2017年 / 515卷

关键词：

Accent recognition; Speech recognition; Deep belief networks; FEATURE-EXTRACTION;

D O I：

10.1007/978-981-10-3153-3_10

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Accent and Emotion recognition for speech has become most important research area because of the increased demand of speech processing systems in handheld devices. Most of the research in speech processing is done for the English language only. In this paper, we present accent recognition system for Telugu speeches. Three important accents of Telugu were chosen and text-dependent speeches of Coastal Andhra, Rayalaseema, and Telangana accents were collected. Features like tonal power ratio, spectral flux, pitch chroma, and MFCC were extracted from these speeches. deep belief networks are used for the classification purpose. The recognition accuracy obtained in this work is 93%.

引用

页码：99 / 105

页数：7

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