Naturalistic Head Motion Generation from Speech

Trisha Mittal; Zakaria Aldeneh; Masha Fedzechkina; Anurag Ranjan; Barry-John Theobald

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arXiv · 2210.14800

Naturalistic Head Motion Generation from Speech

Trisha Mittal·Zakaria Aldeneh·Masha Fedzechkina·Anurag Ranjan·Barry-John Theobald

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Abstract

Synthesizing natural head motion to accompany speech for an embodied conversational agent is necessary for providing a rich interactive experience. Most prior works assess the quality of generated head motion by comparing them against a single ground-truth using an objective metric. Yet there are many plausible head motion sequences to accompany a speech utterance. In this work, we study the variation in the perceptual quality of head motions sampled from a generative model. We show that, despite providing more diverse head motions, the generative model produces motions with varying degrees of perceptual quality. We finally show that objective metrics commonly used in previous research do not accurately reflect the perceptual quality of generated head motions. These results open an interesting avenue for future work to investigate better objective metrics that correlate with human perception of quality.

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BibTeX RIS

Trisha Mittal, Zakaria Aldeneh, Masha Fedzechkina, Anurag Ranjan, Barry-John Theobald. 2022-10-26. Naturalistic Head Motion Generation from Speech. https://arxiv.org/abs/2210.14800

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