MultiTalk: Enhancing 3D Talking Head Generation Across Languages with Multilingual Video Dataset

• URL: http://arxiv.org/abs/2406.14272v1
• Date: Thu, 20 Jun 2024 12:52:46 GMT
• Title: MultiTalk: Enhancing 3D Talking Head Generation Across Languages with Multilingual Video Dataset
• Authors: Kim Sung-Bin, Lee Chae-Yeon, Gihun Son, Oh Hyun-Bin, Janghoon Ju, Suekyeong Nam, Tae-Hyun Oh,
• Abstract summary: We introduce a novel task to generate 3D talking heads from speeches of diverse languages. We collect a new multilingual 2D video dataset comprising over 420 hours of talking videos in 20 languages. We present a metric for assessing lip-sync accuracy in multilingual settings.
• Score: 14.026893125215912
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent studies in speech-driven 3D talking head generation have achieved convincing results in verbal articulations. However, generating accurate lip-syncs degrades when applied to input speech in other languages, possibly due to the lack of datasets covering a broad spectrum of facial movements across languages. In this work, we introduce a novel task to generate 3D talking heads from speeches of diverse languages. We collect a new multilingual 2D video dataset comprising over 420 hours of talking videos in 20 languages. With our proposed dataset, we present a multilingually enhanced model that incorporates language-specific style embeddings, enabling it to capture the unique mouth movements associated with each language. Additionally, we present a metric for assessing lip-sync accuracy in multilingual settings. We demonstrate that training a 3D talking head model with our proposed dataset significantly enhances its multilingual performance. Codes and datasets are available at https://multi-talk.github.io/.

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