Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech
Fig 3
Simulation results for different model designs.
Top row: A 400 cents up-shift in the first formant frequency (F1) was applied from trial 21 to trial 140 (yellow shaded area). To extract F1 for each trial, we averaged F1 of the middle 10 time steps (time step 11 to 20) of the 30 time steps of the simulated acoustic data for each production. Experimental data was retrieved from the control group in Kim & Max [19]. Middle row: F1 values produced across time during five early perturbation trials (trials 22, 24, 26, 28, and 30). Lighter shades indicate later trials. Note that the first 10 time steps for each trial are pre-phonatory preparatory movements from the model’s default start position, so no acoustic data are plotted. Bottom row: The true articulatory state of tongue height (solid green lines) and its state estimate (gray dots), expressed in the Maeda Principal Component unit (M), plotted across time steps for the early perturbation trials (trials 22, 24, 26, 28, and 30). Black dots indicate the estimate in a baseline trial. Lighter shades indicate later trials. In Design A, the estimate diverged from the true state across the time steps, and the amount of divergence also gradually increased across the trials. Only in Design C, the true articulatory state for the tongue height demonstrated noticeable adaptation across trials (green lines). The estimates (gray dots) closely tracked their true state in Design C.