Speaker Recognition Method Combining FFT, Wavelet Functions and Neural Networks
The method of speaker recognition based on wavelet functions and neural networks is presented in this paper. The wavelet functions are used to obtain the approximation function and the details of the speaker’s averaged spectrum in order to extract speaker’s voice characteristics from the frequency spectrum. The approximation function and the details are then used as input data for decision-making neural networks. In this recognition process, not only the decision on the speaker’s identity is made, but also the probability that the decision is correct can be provided.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is temporarily free for AES members.