A comparison of auditory and blind separation techniques for speech segregation

A fundamental problem in auditory and speech processing is the segregation of speech from concurrent sounds. This problem has been a focus of study in computational auditory scene analysis (CASA), and it has also been recently investigated from the perspective of blind source separation. Using a standard corpus of voiced speech mixed with interfering sounds, we report a comparison between CASA and blind source separation techniques, which have been developed independently. Our comparison reveals that they perform well under very different conditions. A number of conclusions are drawn with respect to their relative strengths and weaknesses in speech segregation applications as well as in modeling auditory function.