Proceedings ArticleDOI
An efficient text dependent speaker recognition using fusion of MFCC and SBC
K. V. Krishna Kishore,Syed. Sharrefaunnisa,S. Venkatramaphanikumar +2 more
- pp 18-22
TLDR
The proposed method outperforms other existing methods for the recognition of a speaker based on text dependent speech and is validated on a self generated corpus of size 300 samples of 20 individual.Abstract:
In this paper an efficient approach for the recognition of a speaker based on text dependent speech is presented. Speaker Recognition/ Verification system suffers with wide variety of problems. In the proposed approach, the features are extracted using two methods such as Mel Frequency Cepstral Coefficients and wavelet subband coefficients, and then these futures are fused through concatenation to give optimum performance. Those concatenated feature set are more reliable to discriminate an imposter from the genuine. Those concatenated features are classified using support vector machine classifier. Performance of the proposed approach is validated on a self generated corpus of size 300 samples of 20 individual. The proposed method outperforms other existing methods.read more
Citations
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Improved MFCC-Based Feature for Robust Speaker Identification
TL;DR: The logarithmic transformation in the standard MFCC analysis is replaced by a combined function to improve the noisy sensitivity and the proposed robust MFCC-based feature significantly reduces the recognition error rate over a wide signal-to-noise ratio range.
Journal ArticleDOI
Multitaper MFCC and normalized multitaper phase-based features for speaker verification
TL;DR: This work proposes a phase information extraction method that normalizes the change variation in multitaper phase according to the frame position of the input speech to reduce the uncertainty of multitapers phase information in both the state-of-the-art Gaussian mixture model-universal background model (GMM-UBM) baseline and the i-vector speaker verification system.
Proceedings ArticleDOI
Speaker verification with optimized feature subset using MOBA
TL;DR: A novel feature subset selection algorithm is proposed using Bat algorithm and Multi Objective Optimization technique and results shows the proposed algorithm surpassed the accuracy rates shown by the conventional systems.
Journal ArticleDOI
Wavelet detail coefficient as a novel wavelet-mfcc features in text-dependent speaker recognition system
TL;DR: This research proposed the use of a combination of Wavelet and Mel Frequency Cepstral Coefficient (MFCC), Wavelet-MFCC, as feature extraction methods, and Hidden Markov Model (HMM) as classification as classification for speaker recognition.
Sistema de identificación de locutor texto dependiente en Raspberry PI 3 B con aplicación en control de acceso.
TL;DR: In this article, a sistema de reconocimiento de locutor texto dependiente con base a los coeficientes cepstrales of la voz utilizando una Raspberry Pi 3 B, in conjunto with una tarjeta de audio USB and un microfono con conexion tipo jack of 3.5mm.
References
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Journal ArticleDOI
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