Speaker recognition with neural networks.

Speaker recognition with recurrent neural networks

We report on the application of recurrent neural nets in a openset text-dependent speaker identification task. The motivation for applying recurrent neural nets to this domain is to find out if their ability to take short-term spectral features but yet respond to long-term temporal events is advantageous for speaker identification. We use a feedforward net architecture adapted from that introdu...

Comparison of Neural Networks for Speaker Recognition

In a world where authentication and privacy are taking a lot of our daily efforts, it is becoming more important for us to prove our identity to different systems every day so that we can access required and useful services. The problem addressed in this research is speaker verification as it involves knowing the identity of a given speaker using a predefined set of samples. The steps of this p...

Automatic Speaker Recognition Using Neural Networks

Concurrent Neural Networks for Speaker Recognition

We propose a new recognition model called Concurrent Neural Networks (CNN), representing a winner-takes-all collection of neural networks. Each network of the system is trained individually to provide best results for one class only. We have applied the above model for the task of speaker recognition. We performed distinct speaker recognition experiments using three variants of basic components...

Speaker Recognition Using Neural Tree Networks

A new classifier is presented for text-independent speaker recognition. The new classifier is called the modified neural tree network (MNTN). The NTN is a hierarchical classifier that combines the properties of decision trees and feed-forward neural networks. The MNTN differs from the standard NTN in that a new learning rule based on discriminant learning is used, which minimizes the classifica...