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Speech synthesis and voice conversion techniques can pose threats to current speaker verification (SV) systems. For this purpose, it is essential to develop front end systems that are able to distinguish human speech vs. spoofed speech (synthesized or voice converted). In this paper, for the ASVspoof 2015 challenge, we propose a detector based on(More)
Most of the state-of-the-art voice biometrics systems use the natural speech signal (either read speech or spontaneous or contextual speech) from the subjects. In this paper, an attempt is made to identify speakers from their hum. A new feature set, viz., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC) is proposed for this(More)
In this paper, an attempt is made to compare and analyze the various waveform fractal dimension techniques for voice pathology classification. Three methods of estimating the fractal dimension directly from the time-domain waveform have been compared. The methods used are Katz algorithm, Higuchi algorithm and the Hurst exponent calculated using the rescaled(More)
Teager Energy Operator (TEO) proposed by Kaiser and Teager is based on a definition of energy required to generate the signal. TEO gives us the running estimate of energy as a function of amplitude and instantaneous frequency content of the signal. However, it considers three consecutive samples to calculate the energy estimate. In this paper, we suggests(More)