Two-Microphone Separation of Speech Mixtures

Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by the assumption of at least as many sensors as sources. Further, many methods require that the number of signals within the recorded mixtures be known in advance. In many real-world applications, these limitations are too restrictive. We propose a novel method for underdetermined blind source separation using an instantaneous mixing model which assumes closely spaced microphones. Two source separation techniques have been combined, independent component analysis (ICA) and binary time

• Type: Journal
• Year: 2008
• Where: TNN
• Authors: Michael Syskind Pedersen, DeLiang Wang, Jan Larsen, Ulrik Kjems
• Keywords: Source Separation, Source Separation Tasks, Speech Signals, TNN 2008