Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A source signal is estimated using an associative memory model (AMM) and used for separation matrix optimization in linear blind source separation (BSS) to yield high quality and less distorted speech. Linear-filtering-based BSS, such as independent vector analysis (IVA), has been shown to be effective in sound source separation while avoiding non-linear signal distortion. This technique, hover, requires several assumptions of sound sources being independent and generated from non-Gaussian distribution.  propose a method for estimating a linear separation matrix without any assumptions about the sources by repeating the following two steps: estimating non-distorted reference signals by using an AMM and optimizing the separation matrix to minimize an error beten the estimated signal and reference signal. Experimental comparisons carried out in simultaneous speech separation suggest that the proposed method can reduce the residual distortion caused by IVA.
['Motoi Omachi', 'Tetsuji Ogawa', 'Tetsunori Kobayashi', 'Masaru Fujieda', 'Kazuhiro Katagiri']
I am writing a research paper on a idea Separation matrix optimization using associative memory model for blind source separation
[{"from": "human", "value": "I am writing a research paper on a idea Separation matrix optimization using associative memory model for blind source separation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A source signal is estimated using an associative memory model (AMM) and used for separation matrix optimization in linear blind source separation (BSS) to yield high quality and less distorted speech. Linear-filtering-based BSS, such as independent vector analysis (IVA), has been shown to be effective in sound source separation while avoiding non-linear signal distortion. This technique, hover, requires several assumptions of sound sources being independent and generated from non-Gaussian distribution.  propose a method for estimating a linear separation matrix without any assumptions about the sources by repeating the following two steps: estimating non-distorted reference signals by using an AMM and optimizing the separation matrix to minimize an error beten the estimated signal and reference signal. Experimental comparisons carried out in simultaneous speech separation suggest that the proposed method can reduce the residual distortion caused by IVA."}]