Gender discrimination and awareness are essentially practiced in social, education, workplace, economic sectors across the globe. A person manifests this attribute naturally gait, body gesture, facial, including speech. For that reason, automatic gender recognition (AGR) has become an interesting sub-topic speech systems can be found many technology applications. However, retrieving salient gen...

<span lang="EN-US">Speech recognition is one of the important applications artificial intelligence (AI). Speech aims to recognize spoken words regardless who speaking them. The process voice involves extracting meaningful features from and then classifying these into their classes. This paper presents a neural network classification system for Arabic letters. will study effect changing mu...

This paper presents new Speaker Identification and Speaker Verification systems based on the use of new feature vectors extracted from the speech signal. The proposed structure combine between the most successful Mel Frequency Cepstral Coefficients and new features which are the Short Time Zero Crossing Rate of the signal. A comparison between speaker recognition systems based on Gaussian mixtu...

Music genre classification has a significant role in information retrieval for the organization of growing collections music. It is challenging to classify music with reliable accuracy. Many methods have utilized handcrafted features identify unique patterns but are still unable determine original characteristics. Comparatively, using deep learning models been shown be dynamic and effective. Am...

The mel-scaled frequency cepstral coefficients (MFCCs) derived from Fourier transform and filter bank analysis are perhaps the most widely used front-ends in state-of-the-art speech recognition systems. One of the major issues with the MFCCs is that they are very sensitive to additive noise. To improve the robustness of speech front-ends with respect to noise, we introduce, in this paper, a new...

This paper presents a novel objective evaluation technique for statistical parametric speech synthesis. One of its novel features is that it focuses on the association between dimensions within the spectral features. We first use a maximal information coefficient to analyze the relationship between subjective scores and associations of spectral features obtained from natural and various types o...

We propose a wideband CELP-type speech coder at 16 kb/s based on a mel-generalized cepstral (MGC) analysis technique. MGC analysis makes it possible to obtain a more accurate representation of spectral zeros compared to linear predictive (LP) analysis and take a perceptual frequency scale into account. A major advantage of the proposed coder is that the benefits of MGC representation of speech ...