Microphone Array Beamforming Approach to Blind Speech Separation

In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set. Key words: Speech Separation, Microphone Array, Speech Recognition

• Type: Conference
• Year: 2007
• Where: MLMI
• Authors: Ivan Himawan, Iain McCowan, Mike Lincoln
• Keywords: Machine Learning, Microphone, Microphone Array, MLMI 2007, Speech Separation