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English(EN) Arti-JEPA: Adapting Video World Model to Real-Time MRI of the Vocal Tract for Speech-Production Analysis

新的Arti-JEPA模型将视频模型适配于声谱图MRI分析

研究人员开发了Arti-JEPA,一种新的联合嵌入预测架构,旨在对声谱图的实时MRI数据进行建模,以进行语音分析。该模型在约62小时的无标签声谱图视频上进行了训练,并在包括音素预测、流畅与不流畅语音分类以及手术后语音变化特征描述等任务上进行了评估。研究结果表明,时间视频先验比逐帧编码器更有效,并且领域适应对于音素预测等某些任务至关重要,尽管它并未改善口吃分类。Arti-JEPA证明了从术后语音中解码音素信号的能力,表明其作为语音科学可重复使用的测量工具的潜力。 AI

影响 这项研究提供了一种使用MRI分析声谱图动力学的新方法,有望推动语音科学和临床应用。

排序理由 该集群包含一篇详细介绍新模型及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新的Arti-JEPA模型将视频模型适配于声谱图MRI分析

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该集群包含一篇详细介绍新模型及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hong Nguyen, Sean Foley, Christina Hagedorn, Yijing Lu, Sudarsana Reddy Kadiri, Dani Byrd, Shrikanth Narayanan ·

    Arti-JEPA:将视频世界模型应用于声带实时MRI以进行语音产生分析

    arXiv:2609.09757v1 Announce Type: cross Abstract: Real-time MRI (rtMRI) captures the dynamics of the entire vocal tract during speech, but labeled data are scarce and the modality - single-slice, grayscale, low-resolution - differs substantially from the natural videos that video…