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Traditionally, Blind Speech Separation techniques are computationallyexpensive as they update the demixing matrix at every time frame index, makingthem impractical to use in many Real-Time applications. In this paper, a robustdata-driven two-microphone sound source localization method is used as acriterion to reduce the computational complexity of the Independent VectorAnalysis (IVA) Blind Speech Separation (BSS) method. IVA is used to separateconvolutedly mixed speech and noise sources. The practical feasibility of theproposed method is proved by implementing it on a smartphone device to separatespeech and noise in Real-World scenarios for Hearing-Aid applications. Theexperimental results with objective and subjective tests reveal the practicalusability of the developed method in many real-world applications.

A Computationally Efficient and Practically Feasible Two Microphones Blind Speech Separation Method