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arXiv · 2408.04363

Simulating Articulatory Trajectories with Phonological Feature Interpolation

Angelo Ortiz Tandazo·Thomas Schatz·Thomas Hueber·Emmanuel Dupoux
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Abstract

As a first step towards a complete computational model of speech learning involving perception-production loops, we investigate the forward mapping between pseudo-motor commands and articulatory trajectories. Two phonological feature sets, based respectively on generative and articulatory phonology, are used to encode a phonetic target sequence. Different interpolation techniques are compared to generate smooth trajectories in these feature spaces, with a potential optimisation of the target value and timing to capture co-articulation effects. We report the Pearson correlation between a linear projection of the generated trajectories and articulatory data derived from a multi-speaker dataset of electromagnetic articulography (EMA) recordings. A correlation of 0.67 is obtained with an extended feature set based on generative phonology and a linear interpolation technique. We discuss the implications of our results for our understanding of the dynamics of biological motion.

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Angelo Ortiz Tandazo, Thomas Schatz, Thomas Hueber, Emmanuel Dupoux. 2024-08-08. Simulating Articulatory Trajectories with Phonological Feature Interpolation. https://arxiv.org/abs/2408.04363

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