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The consequences of ignoring correlations between features in traditional forensic speaker recognition are investigated. Two likelihood ratio-based discrimination experiments on the same multivariate formant data are described, one taking correlation into account and the other not doing so. The...
Voice biometric feature extraction is the core task in developing any speaker identification system. This paper proposes a robust feature extraction technique for the purpose of speaker identification. The technique is based on processing monaural speech signal using human auditory system based...
In this paper, the Session Variability Subspace Projection (SVSP) method based on model compensation for speaker verification was improved using the Minimum Mean Square Error (MMSE) criterion. The issue of SVSP is that the speaker's session-independent supervector is approximated by the average...
Conventional Speaker Identification (SI) systems utilise spectral features like Mel-Frequency Cepstral Coefficients (MFCC) or Perceptual Linear Prediction (PLP) as a frontend module. Line Spectral pairs Frequencies (LSF) are popular alternative representation of Linear Prediction Coefficients...
In this paper we proposed a text-independent (TI) speaker identification method that suppresses the phonetic information by a subspace method, under the assumption that a subspace with large variance in the speech feature space is a 'phoneme-dependent subspace' and a complementary subspace of it...
Biometric identification is one of the most developing areas. In this paper, a biometric system is simulated using speech features, which identifies the speaker along with their gender and mental status. Work here is broadly classified into two parts, i.e., extraction of the speech features,...
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