Accent classification in speech

被引：33

作者：

Deshpande, S ^{[1
]}

Chikkerur, S ^{[1
]}

Govindaraju, V ^{[1
]}

机构：

[1] SUNY Buffalo, Ctr Unified Biometr & Sensors, Buffalo, NY 14260 USA

来源：

Fourth IEEE Workshop on Automatic Identification Advanced Technologies, Proceedings | 2005年

关键词：

D O I：

10.1109/AUTOID.2005.10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Apart form the word content and identity of a speaker; speech also conveys information about several soft biometric traits such as accent and gender. Accurate classification of these features can have a direct impact on present speech systems. An accent specific dictionary or word models can be used to improve accuracy of speech recognition systems. Gender and accent information can also be used to improve the performance of speaker recognition systems. In this paper, we distinguish between standard American English and Indian Accented English using the second and third formant frequencies of specific accent markers. A GMM classification is used on the feature set for each accent group. The results show that using just the formant frequencies of these accent markers is sufficient to achieve a suitable classification for these two accent groups.

引用

页码：139 / 143

页数：5