“Controlling a Mobile Robot with Natural Commands based on Voice and Gesture”, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).īarbu, T. R., Jain, S., Jovancevic, I., Suri, Y., Morand, C. The accuracy reached about 82% in voice recognition process with 10 speakers, meanwhile, the highest accuracy was 93% with only 1 speaker.įardana, A. Set of cepstral will be classified according to the speaker, using artificial neural network.
Then the voice characteristic will be extracted using a bark-frequency cepstral coefficient. At first, the voice signal will be separated by a pause signal using voice activity detection. This research is useful for the development of biometric-based security application. We developed the technology to extract voice characteristics of each speaker based on spectral analysis. To identify the speaker, we need to understand the speech signal feature extraction process. The problem is that background noise and signal characteristics of each person which is unique, cause speaker classification process becomes more complex. Voice charactheristic is also used as a tool to identify subjects who are speaking. In daily interactions, human use voice as a tool to communicate with others.
#Register cepstral voices verification#
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