Proposed combination of PCA and MFCC feature extraction in speech recognition system

被引：0

作者：

Hoang Trang ^{[1
]}

Tran Hoang Loc ^{[1
]}

Huynh Bui Hoang Nam ^{[2
]}

机构：

[1] Ho Chi Minh City Univ Technol VNU HCM, Ho Chi Minh City, Vietnam

[2] Ho Chi Minh City Peoples Comm, Ho Chi Minh City, Vietnam

来源：

2014 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC) | 2014年

关键词：

MFCC; PCA; dimesional reduction; speech recognition; HMM;

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：

In speech recognition system, the Mel Frequency Cepstrum Coefficients (i.e. MFCC) feature extraction is an important process. It has also been wildly used in many applications. In this paper, we present the conventional MFCC feature extraction method and propose two novel versions of MFCC method that will combine the PCA technique and conventional MFCC feature extraction method. Finally, these three different MFCC methods will be tested in terms of recognition accuracy and the execution time of the HMM training process. From these two measures (i.e. recognition accuracy and time complexity of HMM training process), the developers can choose the appropriate MFCC method for the speech recognition application.

引用

页码：697 / 702

页数：6

共 50 条

[1] Improved MFCC feature extraction by PCA-optimized filterbank for speech recognition
Lee, SM
Fang, SH
Hung, JW
Lee, LS
[J]. ASRU 2001: IEEE WORKSHOP ON AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING, CONFERENCE PROCEEDINGS, 2001, : 49 - 52
[2] Feature Data Reduction of MFCC Using PCA and SVD in Speech Recognition System
Winursito, Anggun
Hidayat, Risanuri
Bejo, Agus
Utomo, Muhammad Nur Yasir
[J]. 2018 INTERNATIONAL CONFERENCE ON SMART COMPUTING AND ELECTRONIC ENTERPRISE (ICSCEE), 2018,
[3] Denoising Speech for MFCC Feature Extraction Using Wavelet Transformation in Speech Recognition System
Hidayat, Risanuri
Bejo, Agus
Sumaryono, Sujoko
Winursito, Anggun
[J]. PROCEEDINGS OF 2018 THE 10TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING (ICITEE), 2018, : 280 - 284
[4] Hardware Implementation of MFCC Feature Extraction for Speech Recognition on FPGA
Van-Lan Dao
Van-Danh Nguyen
Hai-Duong Nguyen
Van-Phuc Hoang
[J]. ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGY, 2017, 538 : 248 - 254
[5] Hierarchical Speech Recognition System Using MFCC Feature Extraction and Dynamic Spiking RSOM
Tarek, Behi
Najet, Arous
Noureddine, Ellouze
[J]. 2014 15TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD), 2014, : 41 - 46
[6] On the use of kernel PCA for feature extraction in speech recognition
Lima, A
Zen, H
Nankaku, Y
Miyajima, C
Tokuda, K
Kitamura, T
[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2004, E87D (12) : 2802 - 2811
[7] 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,
[8] Arabic Speech Recognition Using MFCC Feature Extraction and ANN Classification
Wahyuni, Elvira Sukma
[J]. 2017 2ND INTERNATIONAL CONFERENCES ON INFORMATION TECHNOLOGY, INFORMATION SYSTEMS AND ELECTRICAL ENGINEERING (ICITISEE): OPPORTUNITIES AND CHALLENGES ON BIG DATA FUTURE INNOVATION, 2017, : 22 - 25
[9] Filterbank Analysis of MFCC Feature Extraction in Robust Children Speech Recognition
Naing, Hay Mar Soe
Miyanaga, Yoshikazu
Hidayat, Risanuri
Winduratna, Bondhan
[J]. 2019 INTERNATIONAL SYMPOSIUM ON MULTIMEDIA AND COMMUNICATION TECHNOLOGY (ISMAC), 2019,
[10] Chip design of MFCC extraction for speech recognition
Wang, JC
Wang, JF
Weng, YS
[J]. INTEGRATION-THE VLSI JOURNAL, 2002, 32 (1-2) : 111 - 131

← 1 2 3 4 5 →