Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robust speaker recognition, which we mainly employ to support MFCC coefficients in noisy environments. Entrocy is the fourier transform of the entropy, a measure of the fluctuation of the information in sound segments over time. Entrocy features are combined with MFCCs to generate a composite feature set which is tested using the gaussian mixture model (GMM) speaker recognition method. The proposed method shows improved recognition accuracy over a range of signal-to-noise ratios.
Evidences indicate that human beings were preoccupied with extreme forms of mental and psychic experiences long before they were recorded in literature. Greek myths and legends appear to include symbolizations of delusions, mania, and other bizarre forms of thought and behaviuor. The figure of the mad man or woman is analogous to the wild man, or the imaginary being who appears in various forms throughout western literature and art. Various studies refer to the notion of the wild man as a response to a persistent psychological urge. This urge gives an external expression and a valid form to the impulses of reckless physical self-assertion which is believed to be hidden in all of us, but is normally kept under control. Such impulses were exp
... Show More—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb
... Show MoreA steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.
In this contribution, density functional theory-based calculations have been carried out to assess the electronic, photocatalytic and optical properties of Ce1-xTixO2 system. Ti incorporation leads to a decrease of Ce 4f states and enhancement of Ti 3d states in the bottom of conduction band. Furthermore, it was found that doping ceria with Ti-like transition metals could evidently shift the absorption of pure CeO2 towards higher wavelength range. These findings can provide some new insights for designing CeO2-based photocatalysts with high photocatalytic performance. To the best of our knowledge, this investigation calculates Mullikan’s charge transfer of Ce1-xTixO2 system for the first time. Charge transfer reveals an ionic bond between
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