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...

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...

This paper presents a set of cepstral parameters based on timevarying linear prediction. The lattice filter structure is utilized to accommodate efficient stabilization of models and a Bark-like warped frequency scale. As the proposed cepstral features are based on non-stationary spectral analysis there is a potential for complementary information not captured in conventional features. In class...

This paper presents a method for enhancing speech signals in the root cepstral domain, typically in conjunction with the cepstral subtraction technique. The effect of the processing is similar to the spectral sharpening method performed in the time domain, but with a much lower computational requirement when combined with cepstral subtraction and with better performance. The portions of the sig...

Artiicial neural networks (ANNs) have been used to classify phonetic features in speech. The feature streams from the ANNs are used here as the observations for Hidden Markov Models (HMMs). Using such observations allows us to build a competitive speech recogniser. This recogniser is compared to a similar recogniser that was trained on mel-frequency cepstral coeecients (MFCCs). While the cepstr...

This paper introduces a novel approach, Cepstral Separation Difference (CSD), for quantification of speech impairment in Parkinson's disease (PD). CSD represents a ratio between the magnitudes of glottal (source) and supra-glottal (filter) log-spectrums acquired using the source-filter speech model. The CSD-based features were tested on a database consisting of 240 clinically rated running spee...

In this paper, we introduce a gear defect detection system using frequency analysis based on deep learning. The existing diagnosis systems acoustic use spectrogram, scalogram, and MFCC (Mel-Frequency Cepstral Coefficient) images as inputs to the convolutional neural network (CNN) model diagnose defects. However, visualized data input CNN models requires lot of computation time. Although computi...

Every person in the world want to share their information, thoughts from one person to another. So communication plays very important role into that. Speech is the primary means of communication. Hindi is very popular and well known language of India. Everybody understands and speak and write easily. Our System developed for Hindi Text to Speech and Speech to Text Conversion mainly into the Hin...