TY - GEN
T1 - Comparative analysis of speaker recognition system based on voice activity detection technique, MFCC and PLP Features
AU - Kalia, Akanksha
AU - Sharma, Shikar
AU - Pandey, Saurabh Kumar
AU - Jadoun, Vinay Kumar
AU - Das, Madhulika
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.
AB - Due to rapid advancement in technology, speaker recognition systems become more robust and user friendly. The idea is to study and analyse the speech signal based on feature extraction method. This paper compares the performance of Mel-Frequency Cepstral Coefficient (MFCC) and PLP feature extraction with voice activity detection (VAD) technique. Vector Quantisation approach is used for features matching to select the combination which gives highest accuracy.
UR - http://www.scopus.com/inward/record.url?scp=85077510319&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077510319&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-0214-9_82
DO - 10.1007/978-981-15-0214-9_82
M3 - Conference contribution
AN - SCOPUS:85077510319
SN - 9789811502132
T3 - Lecture Notes in Electrical Engineering
SP - 781
EP - 787
BT - Intelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018
A2 - Kalam, Akhtar
A2 - Niazi, Khaleequr Rehman
A2 - Soni, Amit
A2 - Siddiqui, Shahbaz Ahmed
A2 - Mundra, Ankit
PB - Springer Paris
T2 - 1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018
Y2 - 22 December 2018 through 23 December 2018
ER -