Calibration is a common practice in image steganalysis for extracting prominent features. Based on the idea of reembedding, a new set of calibrated features for audio steganalysis applications are proposed. These features are extracted from a model that has maximum deviation from human auditory system and had been specifically designed for audio steganalysis. Ability of the proposed system is t...

In this paper, we continue our investigation of the warped discrete cosine transform cepstrum (WDCTC), which was earlier introduced as a new speech processing feature [1]. Here, we study the statistical properties of the WDCTC and compare them with the mel-frequency cepstral coefficients (MFCC). We report some interesting properties of the WDCTC when compared to the MFCC: its statistical distri...

This study proposes a new set of feature parameters based on subband analysis of the speech signal for classi cation of speech under stress. The new speech features are Scale Energy (SE), Autocorrelation-Scale-Energy (ACSE), Subband based cepstral parameters (SC), and Autocorrelation-SC (ACSC). The parameters' ability to capture di erent stress types is compared to widely used Mel-scale cepstru...

Speaker recognition is an ability to identify speaker’s characteristics based from spoken language. The purpose of this study gender speakers on audio recordings. objective evaluate the accuracy rate technique differentiate and also determine performance classify even when using self-acquired Audio forensics uses voice recordings as part evidence solve cases. This mainly conducted provide easie...

This study has been done on a technique which is suitable for tapping the telephonic conversation from a remote location to identify intoxication and consequent impaired brain activity that may cause criminal events e.g. DUI (driving under influence). This technique is time efficient, easy to use, non–invasive for the peoples and affordable for law enforcement personnel, bartenders/servers, cou...

Speaker identification for the speech signal processing request, determining speaker is a challenge due to physical variation. This paper emphasizes new algorithm based on acoustic feature analysis of text-dependent speech. In this proposed method changed by ten variation methods. Acoustic all types voice calculated its arithmetical correlation coefficients and mean value. The audio characteris...

To choose the best features in data mining issues, the Relief Feature Selection Algorithm is proposed to implement the feature selection in this paper. Firstly, the data of Ionosphere from the UCI (University of California Irvine) database is used to do a simulation experiment; secondly, the proposed method is employed to do feature selection for voice signal. In this case study, the study star...

Abstract— In this paper, we study the effect on speaker identification (SI) system when speech data is recorded on two different sensors, a HP Pavilion third generation laptop and a Samsung mobile ( S3770K) both with built-in microphone in parallel in a closed room in noise free environment. The database contains 10 Hindi sentences (50-60 seconds speech) and one english sentence (7-8 seconds sp...

This paper proposes a new investigation on Gaussian mixture model (GMM) by comparing it with some preliminary experiments on multilayered perceptron network (MLP) with backpropagation learning algorithm (BKP) and dynamic time warping (DTW) techniques on Thai text-dependent speaker identification system. Three major identification engines are conducted on 50 speakers with isolated digits 0-9. Tr...

This paper describes an HMM based speaker verification system, which verifies speakers in their own specific feature space. This ‘individual’ feature space is determined by a Dynamic Programming (DP) feature selection algorithm. A suitable criterion, correlated with Equal Error Rate (EER) was developed and is used for this feature selection algorithm. The algorithm was evaluated on a text-depen...