New generation of speech coders have to achieve two goals: efficient use of bandwidth and high speech quality. The objective of this thesis is to improve the modelling of speech signal within the constraints of a low bit rate coder. Many speech coding algorithms use Linear Prediction (LP) coefficients to describe the power spectrum of the speech. These parameters are obtained for blocks of inpu...

A technique that uses linear prediction and system identification to achieve noise reduction in a voice signal mixed with a background noise is proposed. In this method, the linear prediction error filter (LPEF) whose coefficients will converge such that the prediction error signal becomes white, removes the spectrum of the voice from a voice mixed with noise. Thereby, the prediction error sign...

In this paper, a new method is presented that offers efficient computation of Linear Prediction Coefficients (LPC) via a new Recursive Least Squares (RLS) adaptive filtering algorithm. This method can be successfully used in speech coding and processing. The introduced algorithm is numerically robust, fast, parallelizable and has particularly good tracking properties. By means of this scheme, L...

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...

In this paper music genre classification has been explored with special emphasis on the decision time horizon and ranking of tappeddelay-line short-time features. Late information fusion as e.g. majority voting is compared with techniques of early information fusion1 such as dynamic PCA (DPCA). The most frequently suggested features in the literature were employed including melfrequency cepstra...

Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients (LFCCs) and Relative Spectral Perceptual Linear Prediction (RASTA-PLP). In this study, Spectral Subband Centroids (SSCs) are examined. These features are the centroid...

bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. therefore, correct prediction of bankruptcy is of high importance in the financial world. this research intends to investigate financial crisis prediction power using models based on neural network...

We propose an effective feature extraction technique for obtaining essential time-frequency information from the linear prediction (LP) residual signal, which are closely related to the glottal vibration of individual speaker. With pitch synchronous analysis, wavelet transform is applied to every two pitch cycles of the LP residual signal to generate a new feature vector, called Wavelet Based F...