Figure 5.

(Color online) Schematic illustrating the proposed cNMFsc algorithm. The input matrix V can be constructed either from real (EMA) or synthesized (TaDA) articulatory data. In this example, we assume that there are M = 7 articulator fleshpoint trajectories. We would like to find K = 5 basis functions or articulatory primitives, collectively depicted as the big red cuboid (representing a three-dimensional matrix W). Each vertical slab of the cuboid is one primitive (numbered 1 to 5). For instance, the white tube represents a single component of the third primitive that corresponds to the first articulator (T samples long). The activation of each of these five time-varying primitives/basis functions is given by the rows of the activation matrix H in the bottom right hand corner. For instance, the five values in the tth column of H are the weights which multiply each of the five primitives at the tth time sample.