AUTOMATIC LANGUAGE IDENTIFICATION OF THREE INDIAN LANGUAGES USING VECTOR QUANTIZATION

被引：0
|
作者：
Roy, Pinki [1 ]
Das, Pradip K. [2 ]
机构：
[1] NIT Silchar, Silchar, Assam, India
[2] IIT Guwahati, Gauhati, Assam, India
来源：
FOURTH INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING (ICCEE 2011) | 2011年
关键词：
Language Identification; Vector Quantization; LPC; Mean Square Error;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The main aim of this paper is to carry out automatic identification of Indian languages using vector quantization. In this particular work we have applied vector quantization classification technique on LPC derived features for identifying 3 Indian languages Assamese, Bengali and Indian English. Experimental results show that recognition accuracy for Assamese & Indian English is better compared to Bengali language. Stop words were used for reducing the overhead of testing process and it shows that Assamese gives optimal recognition rate at 67 % and Bengali, Indian English gives 100% recognition rate. It has also been observed here from mean square error that quality of speech signal used here is very good.
引用
收藏
页码：293 / +
页数：2
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