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In this work we propose novel joint and sequential multimodal approaches for the task of single channel audio source separation in videos. This is done within the popular non-negative matrix factorization framework using information about the sounding object's motion. Specifically, we present methods that utilize non-negative least squares formulation to couple motion and audio information. The proposed...
In this paper we tackle the problem of single channel audio source separation driven by descriptors of the sounding object's motion. As opposed to previous approaches, motion is included as a soft-coupling constraint within the nonnegative matrix factorization framework. The proposed method is applied to a multimodal dataset of instruments in string quartet performance recordings where bow motion...
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