| Title | Voice Recognition Based Security System Using Convolutional Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Chandankhede, Pankaj H., Titarmare, Abhijit S., Chauhvan, Sarang |
| Conference Name | 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) |
| Keywords | ANN (Artificial Neural Network), ASR (Artificial Speech Recognition), CNN (Convolutional Neural Network), composability, convolution, convolutional neural networks, Cross Layer Security, GUI (Graphic User Interface), Human Behavior, human factors, Internet, Metrics, MFCC (Mel-Frequency Cepstrum Coefficients), multifactor authentication, pubcrawl, resilience, Resiliency, security, speech coding, Speech recognition, statistical analysis, STT (Speech-to-Text) |
| Abstract | Following review depicts a unique speech recognition technique, based on planned analysis and utilization of Neural Network and Google API using speech’s characteristics. Multifactor security system pioneered for the authentication of vocal modalities and identification. Undergone project drives completely unique strategy of independent convolution layers structure and involvement of totally unique convolutions includes spectrum and Mel-frequency cepstral coefficient. This review takes in the statistical analysis of sound using scaled up and scaled down spectrograms, conjointly by exploitation the Google Speech-to-text API turns speech to pass code, it will be cross-verified for extended security purpose. Our study reveals that the incorporated methodology and the result provided elucidate the inclination of research in this area and encouraged us to advance in this field. |
| DOI | 10.1109/ICCCIS51004.2021.9397151 |
| Citation Key | chandankhede_voice_2021 |
Voice Recognition Based Security System Using Convolutional Neural Network