In this paper, we propose a peak-weighted cepstral lifter (PWL) for enhancing the spectral peaks of an all-pole model spectrum in the cepstral domain. The design parameter of the PWL is the degree of pole enhancement or pole shifting toward the unit circle. The optimal pole shifting factor is chosen by considering the sensitivity to spectral resonance peaks, the variability of cepstral variance...

In this paper, the performance of several algorithms for the quantization of the mel-generalized cepstral coe cients is studied. First, the objective and subjective performance of two-stage vector quantization (VQ) is measured. It is shown that subjective quality for the mel-generalized cepstral coe cients is higher than that for LSP. Secondly, interframe prediction is introduced in the encodin...

In this letter, we propose a novel approach to feature compensation performed in the cepstral domain. Processing in the cepstral domain has the advantage that the spectral correlation among different frequencies is taken into consideration. By introducing a linear approximation with diagonal covariance assumption, we modify the conventional log-spectral domain feature compensation technique to ...

Cepstral features have been widely used in audio applications. Domain knowledge has played an important role in designing different types of cepstral features proposed in the literature. In this paper, we present a novel approach for learning optimized cepstral features directly from audio data to better discriminate between different categories of signals in classification tasks. We employ mul...

The generalized cepstral analysis method is viewed as a unified approach to the cepstral method and the linear prediction method, in which the model spectrum varies continuously from all-pole to cepstral according to the value of a parameter γ. Since the human ear has high resolution at low frequencies, introducing similar characteristics to the model spectrum, we can represent speech spectrum ...

Currently, one of the most widely used distance measures in speech and speaker recognition is the Euclidean distance between mel frequency cepstral coefficients (MFCC). MFCCs are based on filter bank algorithm whose filters are equally spaced on a perceptually motivated mel frequency scale. The value of mel cepstral vector, as well as the properties of the corresponding cepstral distance, are d...

This paper describes several new cepstral-based compensation procedures that render the SPHINX-II system more robust with respect to acoustical environment. The first algorithm, phonedependent cepstral compensation, is similar in concept to the previously-described MFCDCN method, except that cepstral compensation vectors are selected according to the current phonetic hypothesis, rather than on ...

The automatic speaker verification spoofing and countermeasures challenge 2015 provides a common framework for the evaluation of spoofing countermeasures or anti-spoofing techniques in the presence of various seen and unseen spoofing attacks. This contribution proposes a system consisting of amplitude, phase, linear prediction residual, and combined amplitude phase-based countermeasures for the...