In this chapter, we describe a new framework of blind source separation (BSS), i.e., Single-Input Multiple-Output (SIMO)-model-based ICA (SIMO-ICA), and we discuss its applicability to acoustic signal processing. The term “SIMO” represents a specific transmission system in which the input is a single source signal and the outputs are its transmitted signals observed at multiple microphones. The SIMO-ICA consists of multiple ICAs and a fidelity controller, and each ICA runs in parallel under the fidelity control of the entire separation system. In the SIMOICA scenario, unknown multiple source signals which are mixed through unknown acoustical transmission channels are detected at the microphones, and these signals can be separated, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated signals of the SIMO-ICA can maintain the spatial qualities of each sound source. This attractive feature of the SIMO-ICA shows the promise of applicability to many high-fidelity acoustic signal processing systems. As a good examples of SIMO-ICA’s application, binaural signal separation and blind separation–deconvolution processing are described.
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Saruwatari, H., Takatani, T., Shikano, K. (2007). SIMO-Model-Based Blind Source Separation – Principle and its Applications. In: Makino, S., Sawada, H., Lee, TW. (eds) Blind Speech Separation. Signals and Communication Technology. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6479-1_5
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