Repetition Detection in Stuttered Speech

被引：10

作者：

Ramteke, Pravin B. ^{[1
]}

Koolagudi, Shashidhar G. ^{[1
]}

Afroz, Fathima ^{[1
]}

机构：

[1] Natl Inst Technol Karnataka, Surathkal 575025, Karnataka, India

来源：

PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, NETWORKING AND INFORMATICS (ICACNI 2015), VOL 1 | 2016年 / 43卷

关键词：

MFCCs; Formants; Shimmer; Jitter; Dynamic time warping; CLASSIFICATION;

D O I：

10.1007/978-81-322-2538-6_63

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper mainly focuses on detection of repetitions in stuttered speech. The stuttered speech signal is divided into isolated units based on energy. Mel-frequency cepstrum coefficients (MFCCs), formants and shimmer are used as features for repetition recognition. These features are extracted from each isolated unit. Using Dynamic Time Warping (DTW) the features of each isolated unit are compared with those subsequent units within one second interval of speech. Based on the analysis of scores obtained from DTW a threshold is set, if the score is below the set threshold then the units are identified as repeated events. Twenty seven seconds of speech data used in this work, consists of 50 repetition events. The result shows that the combination of MFCCs, formants and shimmer can be used for the recognition of repetitions in stuttered speech. Out of 50 repetitions, 47 are correctly identified.

引用

页码：611 / 617

页数：7

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