Biometric-based recognition systems have emerged as a prominent field of research and development because of the increasing need for secure and reliable identification and authentication methods. Biometrics has proven to be an effective means of establishing identity and enhancing security across various applications. It identifies research gaps in finger-vein and voice-based biometric systems over recent years. It reviews traditional methodologies and their results and highlights state-of-the-art work in finger-vein and voice biometrics using machine learning and deep learning techniques. The main focus of this proposed work is taking an untouched environment that includes audio and finger-vein. Limitations of unimodal systems, architecture for unimodal and multimodal biometric systems, various methods of feature extraction of an audio and finger-vein biometric trait, and speaker recognition techniques are described in this paper. It reviews audio and finger-vein-based biometric systems for the last decade.