Noise Robust Speech Recognition System using Mel Cepstral and Genetic Algorithm

被引：0

作者：

Mamta, Garg ^{[1
]}

Shatru, Arora Ajat ^{[2
]}

Savita, Gupta ^{[3
]}

机构：

[1] St Longowal Inst Engn & Technol, Dept Comp Sci & Engn, Longowal, India

[2] St Longowal Inst Engn & Technol, Dept Elect & Instrumentat Engn, Longowal, India

[3] Panjab Univ, Univ Inst Engn & Technol, Dept Comp Sci & Engn, Chandigarh, India

来源：

2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, AND OPTIMIZATION TECHNIQUES (ICEEOT) | 2016年

关键词：

MFCC; Speech Recognition; Genetic Algorithm; FAR; FRR; Accuracy; MFCC;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper suggested a technique based on MFCC analysis for audio signals with speech classification application. The proposed work used multi-resolution (wavelet) analysis and spectral analysis based features for feature extraction. The proposed approach uses a no. of features like Mel Frequency Cepstral Coefficient (MFCC), and FFT Coefficients combined with wavelet based features. In addition, accuracy of 99% using the proposed work is claimed.

引用

页码：3151 / 3155

页数：5

共 50 条

[1] Cepstral gain normalization for noise robust speech recognition
Yoshizawa, Shingo
Hayasaka, Noboru
Wada, Naoya
Miyanaga, Yoshikazu
[J]. ICASSP IEEE Int Conf Acoust Speech Signal Process Proc, 1600, (I209-I212):
[2] Robustness of speech recognition using genetic algorithms and a Mel-cepstral subspace approach
Selouani, SA
O'Shaughnessy, D
[J]. 2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING, 2004, : 201 - 204
[3] CEPSTRAL NOISE SUBTRACTION FOR ROBUST AUTOMATIC SPEECH RECOGNITION
Rehr, Robert
Gerkmann, Timo
[J]. 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 375 - 378
[4] Cepstral gain normalization for noise robust speech recognition
Yoshizawa, S
Hayasaka, N
Wada, N
Miyanaga, Y
[J]. 2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING, 2004, : 209 - 212
[5] Cepstral amplitude range normalization for noise robust speech recognition
Yoshizawa, S
Hayasaka, N
Wada, N
Miyanaga, Y
[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2004, E87D (08): : 2130 - 2137
[6] A Cepstral PDF Normalization Method for Noise Robust Speech Recognition
Suk, Yong Ho
Choi, Seung Ho
[J]. ADVANCES IN COMPUTER SCIENCE, ENVIRONMENT, ECOINFORMATICS, AND EDUCATION, PT II, 2011, 215 : 34 - +
[7] Improved DTW Speech Recognition Algorithm Based on the MEL Frequency Cepstral Coefficients
Wei Ming-zhe
Li Xi
Ren Li-mian
[J]. 12TH ANNUAL MEETING OF CHINA ASSOCIATION FOR SCIENCE AND TECHNOLOGY ON INFORMATION AND COMMUNICATION TECHNOLOGY AND SMART GRID, 2010, : 235 - 238
[8] FEATURE EXTRACTION ALGORITHM USING NEW CEPSTRAL TECHNIQUES FOR ROBUST SPEECH RECOGNITION
Korba, Mohamed Cherif Amara
Bourouba, Houcine
Djemili, Rafik
[J]. MALAYSIAN JOURNAL OF COMPUTER SCIENCE, 2020, 33 (02) : 90 - 101
[9] Speech recognition system using enhanced mel frequency cepstral coefficient with windowing and framing method
Lokesh, S.
Devi, M. Ramya
[J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 5): : 11669 - 11679
[10] Speech recognition system using enhanced mel frequency cepstral coefficient with windowing and framing method
S. Lokesh
M. Ramya Devi
[J]. Cluster Computing, 2019, 22 : 11669 - 11679

← 1 2 3 4 5 →