identifying an unknown language from the test utterances. In this paper, a new method of feature extraction, viz., Teager Energy Based Mel Frequency Cepstral Coefficients (T-MFCC) is developed for identification of perceptually similar languages. Finally, an LID system is presented for Hindi and Urdu (perceptually similar Indian languages) to demonstrate effectiveness of newly proposed feature ...

A method for the estimation of music similarity based on the use of the standardized variogram as clustering algorithm for Mel Frequency Cepstral Coefficients, is detailed in this report. The standardized variogram is used for the compression of the information of MFCCs. The algorithm is submitted to the Audio Music Similarity task of MIREX 2011, in occasion of the 12th ISMIR Conference.

This paper describes the team MTM participation in Violent Scenes Detection (VSD) task of the MediaEval 2014 campaign. We propose an approach to the problem of detecting violence, which is based on probabilistic graphical models using Mel-frequency cepstral coefficients (MFCCs) as audio feature. In our approach, we employ Dynamic Bayesian Networks (DBNs) to represent a violent scene as an dynam...

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 measure perceptual judgments. We determine that a timbre space based on Mel-frequency cepstral coefficients (MFCC) is a good model for perceptual timbre space.

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 measure perceptual judgments on an equivalent range of timbre variety. We determine that a timbre space based on Mel-frequency cepstral coefficients (MFCC) is a good model for a perceptua...

The computerized respiratory sound analysis systems provide vital information concerning the current condition of lung. These systems, used by physicians for diagnosis diseases, help to classify sounds. Because each physician has different knowledge and experience, there is a problem with diagnosing treating system diseases. This study will decide in various difficult diagnostic situations easi...

In this paper we introduce a robust feature extractor, dubbed as Modified Function Cepstral Coefficients (MODFCC), based on gammachirp filterbank, Relative Spectral (RASTA) and Autoregressive Moving-Average (ARMA) filter. The goal of this work is to improve the robustness of speech recognition systems in additive noise and real-time reverberant environments. In speech recognition systems Mel-Fr...

We propose to use a perceptually-oriented domain to improve the quality of text-to-speech generated by deep neural networks (DNNs). We train a DNN that predicts the parameters required for speech reconstruction but whose cost function is calculated in another domain. In this paper, to represent this perceptual domain we extract an approximated version of the SpectroTemporal Excitation Pattern t...