Separation and Recognition of Multiple Sound Source Using Pulsed Neuron Model

Many applications would emerge from the development of artificial systems able to accurately localize and identify sound sources. However, one of the main difficulties of such kind of system is the natural presence of multiple sound sources in real environments. This paper proposes a pulsed neural network based system for separation and recognition of multiple sound sources based on the difference on time lag of the different sources. The system uses two microphones, extracting the time difference between the two channels with a chain of coincidence detection pulsed neurons. An unsupervised neural network processes the firing information corresponding to each time lag in order to recognize the type of the sound source. Experimental results show that three simultaneous musical instruments’ sounds could be successfully separated and recognized.

• Type: Conference
• Year: 2007
• Where: ICANN
• Authors: Kaname Iwasa, Hideaki Inoue, Mauricio Kugler, Susumu Kuroyanagi, Akira Iwata
• Keywords: ICANN 2007, Multiple Sound Sources, Sound Source, Time Lag