Abstract
Humans are able to well recognize mixtures of speech signals produced by two or more simultaneous speakers. This ability is known as cocktail party effect. Applying the cocktail party effect to engineering, we can construct novel systems of blind source separation such as current automatic speech recognition systems and active noise control systems under environment noises. Considering blind source separation as the characteristics of human, artificial neural networks are suitable for it. In this paper, we proposed a method of blind source separation using a neural network. The present neural network can adaptively separate sound sources on training the internal parameters.
Sign-in/Register to access full text options 
Free) 
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
