Separation of acoustic signals using self-organizing neural networks

Spectral modeling is an essential component in many signal processing applications, such as speech enhancement and sound monitoring. This paper demonstrates its use in the separation of acoustic sources from a compound signal that is registered by one sensor. Our technique distinguishes itself from the popular blind source separation procedure by its much higher noise insensitivity and its ability to cope with varying as well as non-square mixing conditions.