Feature Vector Selection of Fusion of MFCC and SMRT Coefficients for SVM Classifier Based Speech Recognition System

被引：0
|
作者：
Mini, P. P. [1 ]
Thomas, Tessamma [1 ]
Gopikakumari, R. [2 ]
机构：
[1] CUSAT, Dept Elect, Kochi, Kerala, India
[2] CUSAT, Sch Engn, Kochi, Kerala, India
来源：
PROCEEDINGS OF THE 2018 8TH INTERNATIONAL SYMPOSIUM ON EMBEDDED COMPUTING AND SYSTEM DESIGN (ISED 2018) | 2018年
关键词：
Speech recognition; SMRT; MFCC; SVM; SPEAKER IDENTIFICATION;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Automatic speech recognition system involves two phases namely training and matching. Features extracted from known speech signals are used to train the system and is matched with the features generated from unknown speech. Selection of good technique for feature extraction and feature matching has a prominent effect in speech recognition. Feature vector selection, from Mel Frequency Cepstral Coefficients (MFCC) and Sequency based Mapped Real Transform (SMRT) coefficients, is presented in this work. Linear kernel based Support Vector Machine (SVM) is used as the classifier for recognizing the speech. The results show that fusion of transform coefficients increases the recognition rate and also the efficiency of the proposed system.
引用
收藏
页码：153 / 157
页数：5
相关论文
共 50 条
  • [1] EEG based direct speech BCI system using a fusion of SMRT and MFCC/ LPCC features with ANN classifier
    Mini, P. P.
    Thomas, Tessamma
    Gopikakumari, R.
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 68
  • [2] Research on Speech Emotion Recognition Based on Teager Energy Operator Coefficients and Inverted MFCC Feature Fusion
    Wang, Feifan
    Shen, Xizhong
    [J]. ELECTRONICS, 2023, 12 (17)
  • [3] Development of a MFCC-SVM Based Turkish Speech Recognition System
    Tombaloglu, Burak
    Erdem, Hamit
    [J]. 2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU), 2016, : 929 - 932
  • [4] Multi-feature Fusion Speech Emotion Recognition Based on SVM
    Zeng, Xiaoping
    Dong, Li
    Chen, Guanghui
    Dong, Qi
    [J]. PROCEEDINGS OF 2020 IEEE 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC 2020), 2020, : 77 - 80
  • [5] Feature Selection for an SVM Based Webpage Classifier
    Mtetwa, Nhamo
    Yousefi, Mehdi
    Reddy, Viseshini
    [J]. 2017 IEEE 4TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI), 2017, : 85 - 88
  • [6] Feature Extraction Using Fusion MFCC For Continuous Marathi Speech Recognition
    Gaikwad, Santosh
    Gawali, Bharti
    Yannawar, Pravin
    Mehrotra, Suresh
    [J]. 2011 ANNUAL IEEE INDIA CONFERENCE (INDICON-2011): ENGINEERING SUSTAINABLE SOLUTIONS, 2011,
  • [7] Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition
    Islam, Md. Rabiul
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2014, 2014
  • [8] A Fast Leaf Recognition Algorithm based on SVM Classifier and High Dimensional Feature Vector
    Di Ruberto, Cecilia
    Putzu, Lorenzo
    [J]. PROCEEDINGS OF THE 2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS (VISAPP), VOL 1, 2014, : 601 - 609
  • [9] A Feature Selection Based Serial SVM Ensemble Classifier
    Cao, Jianjun
    Lv, Guojun
    Chang, Chen
    Li, Hongmei
    [J]. IEEE ACCESS, 2019, 7 : 144516 - 144523
  • [10] Local Projections and Support Vector Based Feature Selection in Speech Recognition
    Miguel, Antonio
    Ortega, Alfonso
    Buera, Luis
    Lleida, Eduardo
    [J]. INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5, 2009, : 48 - 51
12345