Traditionally the use of biometric devices has improved our ability to provide authenticated access to physical installations. Biometrics is the use of a person"s unique physiological, behavioral, and morphological characteristic to provide positive personal identification. Biometric systems that are currently available today examine fingerprints, handprints, iris and retina patterns, and face. Systems that are close to biometrics but are not classified as such are behavioral systems such as voice, signature and keystroke systems. They test patterns of behavior not parts of the body. Over the next few years, the use of biometrics will continue to grow and become much more commonplace.Today the core technologies have evolved and the cost of the equipment is going down dramatically due to the integration and increasing processing power. Certain applications of biometric identification technology are now cost-effective, reliable and highly accurate. As a result, there is no technological or financial barrier for stepping from the pilot projects to widespread deployment. This paper is an attempt to highlights the biometric technologies in concern with human interface.

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The aim of this paper is to develop a flexible framework capable of automatically recognizing phonetic units present in a speech utterance of any language spoken in any mode. In this study, we considered two modes of speech: conversation, and read modes in four Indian languages, namely, Telugu, Kannada, Odia, and Bengali. The proposed approach consists of two stages: (1) Automatic speech mode classification (SMC) and(2) Automatic phonetic recognition using mode-specific multilingual phone recognition system (MPRS). In this work, vocal tract and excitation souce features are considered for speech mode classification (SMC) task. SMC systems are developed using multilayer perceptron (MLP). Further, vocal tract, excitation source, and tandem features are used to build the deep neural network (DNN)-based MPRSs. The performance of the proposed approach is compared with mode-dependent MPRSs. Experimental results show that the proposed approach which combines both SMC and MPRS into a single system outperforms the baseline mode-dependent MPRSs.

Human-computer interaction (HCI) is the study of how people design, implement, and use interactive computer systems and how computers affect individuals, organizations and society. This encompasses not only ease of use but also new interaction techniques for supporting user tasks, providing better access to information, and creating more powerful forms of communication.It involves input and output devices and the interaction techniques that use them; how information is presented and requested; how the computer's actions are controlled and monitored; all forms of help, documentation, and training; the tools used to design, build, test, and evaluate user interfaces; and the processes that developers follow when creating Interfaces. This paper is an attempt to highlights the study of interaction between people (users) and computers.