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English(EN) CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning

新的无编码器音频字幕模型CARD降低了推理成本

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了CARD，一种新颖的无编码器音频字幕模型，通过移除音频编码器显著降低了推理成本。该模型通过将预训练音频教师CLAP-HTSAT的表示策略性地路由到不同组件来蒸馏其知识：将感知阶段路由到投影仪，将语义阶段路由到LLM。这种方法在AudioCaps和Clotho等基准数据集上提高了性能，在推理时无需编码器即可达到55.4分。 AI

影响 这项研究通过降低推理期间的计算需求，可能导致更高效的音频字幕系统。

排序理由 该集群包含一篇详细介绍新模型及其在基准测试中性能的学术论文。

在 arXiv cs.CL 阅读 →

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新的无编码器音频字幕模型CARD降低了推理成本

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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Ganesh Pavan Kartikeya Bharadwaj Kolluri, Yuchen Zhang, Michael Kampouridis, Ravi Shekhar ·

    CARD：用于无编码器音频字幕的跨组件音频表示蒸馏

    arXiv:2607.04619v1 Announce Type: cross Abstract: Modern automated audio captioning systems pair a frozen audio encoder with a large language model (LLM) via a trainable projector, incurring the encoder's inference cost and bottlenecking the model through its fixed acoustic featu…

  2. arXiv cs.CL TIER_1 English(EN) · Ravi Shekhar ·

    CARD：用于无编码器音频字幕的跨组件音频表示蒸馏

    Modern automated audio captioning systems pair a frozen audio encoder with a large language model (LLM) via a trainable projector, incurring the encoder's inference cost and bottlenecking the model through its fixed acoustic features. We present CARD, an encoder-free audio captio…

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