A Comparative Study of the Techniques for Feature Extraction and Classification in Stuttering

被引：0

作者：

Khara, Shweta ^{[1
]}

Singh, Shailendra ^{[2
]}

Vir, Dharam ^{[3
]}

机构：

[1] Punjab Engn Coll, Dept CSE IS, Chandigarh, India

[2] Punjab Engn Coll, Dept CSE, Chandigarh, India

[3] PGIMER, Dept Otolaryngol, Chandigarh, India

来源：

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT) | 2018年

关键词：

Speech Recognition; Stuttering; Feature Extraction; Classification; SPEECH DYSFLUENCIES;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Disability in speech concerns many other communication problems such as hearing, and fluency. Stuttering is a neurodevelopmental disorder identified by the existence of dysfluencies during speech production. The disruptions of speech flow in stuttering have led a large body of researchers to examine the potential processes underlying speech-language production in people who stutter. This paper presents a survey on techniques of feature extraction and classification which are applied for automatic speech recognition, and also presents a comparative analysis of stuttering techniques on the basis of accuracy, sensitivity, specificity, and dataset size.

引用

页码：887 / 893

页数：7

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