In a society where theft is prevalent, ensuring security at every level is crucial. Biometrics is the automated process of identifying individuals based on their unique biological or behavioral characteristics, such as fingerprints, keystrokes, facial features, voices, iris patterns, and gait . Various biometrics methods are used to identify the individuals. Keystroke and Voice biometrics is a technology that uses individuals’ characteristics to identify and authenticate them. Keystroke Dynamics utilizes unique typing rhythm of an individual. Voice Biometrics utilizes unique features of a person’s voice, such as pitch, tone, modulation, and pronunciation, to create a voiceprint similar to a fingerprint . Voice biometrics involves the use of various soft computing techniques to analyze and authenticate voice characteristics. We analyze the importance of accurate speech recognition in voice biometric systems and explore the potential of automated speech conversion. This paper provides a summary of the essential concepts like Ant Colony Optimization, PSO in keystroke dynamics and Spoof net, modeling techniques involved in voice biometrics. Various DNN techniques and obtained results are discussed in this study.