In this paper we study the noise-robustness of mel-frequency cepstral coefficients (MFCCs) and explore ways to improve their performance in noisy conditions. Improvements based on a more accurate model of the early auditory system are suggested to make the MFCC features more robust to noise while preserving their class discrimination ability. Speech versus non-speech classification and speech r...

Gender and age estimation based on Gaussian Mixture Models (GMM) is introduced. Telephone recordings from the Czech SpeechDatEast database are used as training and test data set. Mel-Frequency Cepstral Coefficients (MFCC) are extracted from the speech recordings. To estimate the GMMs’ parameters Maximum Likelihood (ML) training is applied. Consequently these estimations are used as the baseline...

We describe a perceptual space for timbre, define an objective metric that takes into account perceptual orthogonality and measure the quality of timbre interpolation. We discuss two timbre representations and using these two representations, measure perceived relationships between pairs of sounds on a equivalent range of timbre variety. We determine that a timbre space based on Mel-frequency c...

In this paper, a voiced-unvoiced measure is used as acoustic feature for continuous speech recognition. The voiced-unvoiced measure was combined with the standard Mel Frequency Cepstral Coefficients (MFCC) using linear discriminant analysis (LDA) to choose the most relevant features. Experiments were performed on the SieTill (German digit strings recorded over telephone line) and on the SPINE (...

The present investigation analyses the behaviour of the first order derivatives of the log-mel-spectrum of vowels which constitutes the basis for the mel-frequency cepstral coefficients (MFCC). The results indicate that the dynamic features when inspected at log-mel-spectra level seem to be less influenced by speaker specific characteristics and degrade less in fast speech. However, when analys...

The article studies age related variations of speech characteristics of two age groups, in the Bengali language. The study considers 60 speakers in the each age groups, 60– 80 years and 20–40 years, respectively. We have considered different voice source features like fundamental frequency, formant frequencies, jitter, shimmer and harmonic to noise ratio. Cepstral domain feature, Mel Frequency ...

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors...

Reliability of Automatic Speaker Verification (ASV) systems has always been a concern in dealing with spoofing attacks. Among these attacks, replay attack is the simplest and the easiest accessible method. This paper describes a replay spoofing detection system applied to ASVspoof2017 corpus. To reach this goal, features such as Constant-Q Cepstral Coefficients (CQCC), Modified Group Delay (MGD...

Data Science is a fairly novel field, and it predominantly deals with analysis assortment of data. Machine Learning field that goes hand in this regard. Various Algorithms, which are trained on dataset predict results based their training, thus the accuracy model determined by testing dataset. Foreground feature extraction another interesting application. Using data visualization processing, we...