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English(EN) GigaChat Audio: Time-aware Large Audio Language Model

GigaChat Audio 10B 模型提供长达2小时音频的时间感知理解能力

研究人员开发了GigaChat Audio,这是一种新颖的时间感知大型音频语言模型,能够理解长达两小时的音频录音并回答相关问题。该模型通过将周期性时间标记与音频标记交错,解决了长音频中的时间定位挑战。它在时间定位方面取得了显著的准确性,优于其他开源模型,并支持包括自动语音识别(ASR)、翻译和问答在内的各种音频任务。模型权重和数据集正在发布,以促进时间感知音频理解的进一步研究。 AI

影响 该模型推进了音频大型语言模型中的时间定位能力,有望改进需要分析长音频录音的应用。

排序理由 该条目描述了一篇新的研究论文和用于音频理解的模型发布。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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GigaChat Audio 10B 模型提供长达2小时音频的时间感知理解能力

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该条目描述了一篇新的研究论文和用于音频理解的模型发布。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    GigaChat Audio:面向时间的超大音频语言模型

    Temporal grounding in long recordings remains challenging for audio-conditioned LLMs. We present a time-aware audio LLM that answers questions with explicit timestamps over up to 120 minutes of input. Our approach interleaves periodic time markers with continuous audio tokens usi…