Speech-Driven Facial Animations Improve Speech-in-Noise Comprehension of Humans
Varano E, Vougioukas K, Ma P, Petridis S, Pantic M, Reichenbach T (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 15
Article Number: 781196
DOI: 10.3389/fnins.2021.781196
Abstract
Understanding speech becomes a demanding task when the environment is noisy. Comprehension of speech in noise can be substantially improved by looking at the speaker’s face, and this audiovisual benefit is even more pronounced in people with hearing impairment. Recent advances in AI have allowed to synthesize photorealistic talking faces from a speech recording and a still image of a person’s face in an end-to-end manner. However, it has remained unknown whether such facial animations improve speech-in-noise comprehension. Here we consider facial animations produced by a recently introduced generative adversarial network (GAN), and show that humans cannot distinguish between the synthesized and the natural videos. Importantly, we then show that the end-to-end synthesized videos significantly aid humans in understanding speech in noise, although the natural facial motions yield a yet higher audiovisual benefit. We further find that an audiovisual speech recognizer (AVSR) benefits from the synthesized facial animations as well. Our results suggest that synthesizing facial motions from speech can be used to aid speech comprehension in difficult listening environments.
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United Kingdom (GB)How to cite
APA:
Varano, E., Vougioukas, K., Ma, P., Petridis, S., Pantic, M., & Reichenbach, T. (2022). Speech-Driven Facial Animations Improve Speech-in-Noise Comprehension of Humans. Frontiers in Neuroscience, 15. https://dx.doi.org/10.3389/fnins.2021.781196
MLA:
Varano, Enrico, et al. "Speech-Driven Facial Animations Improve Speech-in-Noise Comprehension of Humans." Frontiers in Neuroscience 15 (2022).
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