ANALISIS BIBLIOMETRIK TERHADAP FACE AND VOICE RECOGNITION

Abstract

Technology in the digital age like today, not only makes it easier for humans to interact remotely, but technology is now also widely used as a form of self-recognition. Automatic self-recognition systems are needed in today's information age. Automatic self-recognition can be done using body parts known as biometrics. Biometrics is a self-recognition technology that uses body parts or human behavior. There are several common biometric methods that are often used for self-identification, one of which is face and voice. Therefore, this research aims to find out the development of research with the theme of phase and voice recognition on artificial neural networks from 2019-2023. The type of research used is qualitative with bibliometric analysis. The research used as a search engine is Publish Or Perish (POP) with data collection done through Google Sholar indexed publications. The number of articles analyzed was limited to 200 data in the form of journals. This was done with the aim of narrowing the search for the field of artificial neuroscience, especially in the phase and voice recognition, but only 120 data were fulfilled. The results showed that the most connected topic was neural network. The results of this study can be utilized by future researchers to explore and develop the topic of phase and voice regocnition.