Sound stream segregation: a neuromorphic approach to solve the "cocktail party problem" in real-time.

ABSTRACT: The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the "cocktail party effect." It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently

SUBMITTER: Thakur CS 

PROVIDER: S-EPMC4557082 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature