Abstract

AbstractIn this paper, an automatic speech-speaker recognition system is implemented in real time noisy environment. The database creation with personalized voice in noisy environment is done with microphone arrangement. Various techniques in preprocessing step can be used to remove noise from sampled voice signal. Mel Frequency Cepstral Coefficient (MFCC) technique is used to extract Mel Cepstral Coefficients from each speech sample and thus database is created during training phase. For testing purpose, each input sampled speech signal is mapped with stored database using Vector Quantization (VQ) and Dynamic Time Warping (DTW) techniques. Output of mapped VQ is Speaker Recognition and output of mapped DTW is Speech Recognition. Using single sampled voice, real time Speech and Speaker can be recognized. This system is very useful for various applications such as Forensic, Banking where security is at highest priority.KeywordsMFCCDTWVQFORENSIC

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call