Voice recognition based on MFCC, SBC and Spectrograms

被引:4
作者
Martinez Mascorro, Guillermo Arturo [1 ]
Aguilar Torres, Gualberto [2 ]
机构
[1] Inst Politecn Nacl, Ciencias Ingn Microelect, Mexico City, DF, Mexico
[2] Inst Politecn Nacl, Secc Estudios Posgrad & Invest, ESIME Culhuacan, Mexico City, DF, Mexico
来源
INGENIUS-REVISTA DE CIENCIA Y TECNOLOGIA | 2013年 / 10期
关键词
Speech recognition with voice changes; Mel Frequency Cepstral Coefficients; Subband-Based Cepstral Parameters; Spectrogram; Support Vector Machine;
D O I
10.17163/ings.n10.2013.02
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
One of the problems of the Automatic Speech Recognition systems is the voice's changes. Typically, a person can have voluntary and involuntary voice's changes and the system can get confused in these cases, also the changes could be natural and artificial. This paper proposes and recognition system with a parallel identification, using three different algorithms: MFCC, SBC and Spectrogram. Using a Support Vector Machine as a classifier, every algorithm gives a group of persons with the highest likelihood and, after an evaluation, the result is obtained. The aim of this paper is to take advantage of the three algorithms.
引用
收藏
页码:12 / 20
页数:9
相关论文
共 50 条
[21]   Human Activity Recognition Using Spectrograms of Binary Motion Sensor Data [J].
Seyedtalebi, Nima ;
Silvestri, Simone .
2024 20TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SMART SYSTEMS AND THE INTERNET OF THINGS, DCOSS-IOT 2024, 2024, :377-383
[22]   Investigation of Combined use of MFCC and LPC Features in Speech Recognition Systems [J].
Aida-Zade, K. R. ;
Ardil, C. ;
Rustamov, S. S. .
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 13, 2006, 13 :275-+
[23]   Speaker Verification based on Comparing Normalized Spectrograms [J].
Leu, Jia-Guu ;
Geeng, Liang-tsair ;
Pu, Chang En ;
Shiau, Jyh-Bin .
2011 IEEE INTERNATIONAL CARNAHAN CONFERENCE ON SECURITY TECHNOLOGY (ICCST), 2011,
[24]   An MFCC-based Speaker Identification System [J].
Leu, Fang-Yie ;
Lin, Guan-Liang .
2017 IEEE 31ST INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA), 2017, :1055-1062
[25]   Voice Gender Recognition Using Acoustic Features, MFCCs and SVM [J].
Abakarim, Fadwa ;
Abenaou, Abdenbi .
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2022, PT I, 2022, 13375 :634-648
[26]   ASERNet: Automatic speech emotion recognition system using MFCC-based LPC approach with deep learning CNN [J].
Jagadeeshwar, Kalyanapu ;
Sreenivasarao, T. ;
Pulicherla, Padmaja ;
Satyanarayana, K. N. V. ;
Lakshmi, K. Mohana ;
Kumar, Pala Mahesh .
INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING, 2023, 14 (04)
[27]   Automatic recognition of animal vocalizations using averaged MFCC and linear discriminant analysis [J].
Lee, CH ;
Chou, CH ;
Han, CC ;
Huang, RZ .
PATTERN RECOGNITION LETTERS, 2006, 27 (02) :93-101
[28]   Noisy Speech Training in MFCC-based Speech Recognition with Noise Suppression Toward Robot Assisted Autism therapy [J].
Attawibulkul, Sujirat ;
Kaewkamnerdpong, Boonserm ;
Miyanaga, Yoshikazu .
2017 10TH BIOMEDICAL ENGINEERING INTERNATIONAL CONFERENCE (BMEICON), 2017,
[29]   Voice spoofing detection using a neural networks assembly considering spectrograms and mel frequency cepstral coefficients [J].
Hernández-Nava C.A. ;
Rincón-García E.A. ;
Lara-Velázquez P. ;
de-los-Cobos-Silva S.G. ;
Gutiérrez-Andrade M.A. ;
Mora-Gutiérrez R.A. .
PeerJ Computer Science, 2023, 9
[30]   Voice spoofing detection using a neural networks assembly considering spectrograms and mel frequency cepstral coefficients [J].
Hernandez-Nava, Carlos Alberto ;
Rincon-Garcia, Eric Alfredo ;
Lara-Velazquez, Pedro ;
de-los-Cobos-Silva, Sergio Gerardo ;
Gutierrez-Andrade, Miguel Angel ;
Mora-Gutierrez, Roman Anselmo .
PEERJ COMPUTER SCIENCE, 2023, 9