告诉我，Habibi，它是真的还是假的？
Tell me Habibi, is it Real or Fake?
AI总结：
针对多语言和语码转换语音的深度伪造检测挑战，本文提出了首个大规模阿拉伯语-英语视听深度伪造数据集ArEnAV，包含387k个视频和超过765小时的真实与伪造视频，并利用集成多个TTS和lip-sync模型的新颖管道生成数据，通过基准测试和人类评估展示了其推进深度伪造研究的潜力。
摘要：
深度伪造生成方法发展迅速，使得伪造媒体更难被检测，并引发了严重的社会担忧。大多数深度伪造检测和数据集创建研究集中在单语内容上，往往忽视了多语言和语码转换语音（在同一话语中混合多种语言）的挑战。语码转换，尤其是阿拉伯语和英语之间的转换，在阿拉伯世界很常见，并广泛应用于数字通信。这种语言混合给深度伪造检测带来了额外挑战，因为它可能会使主要在单语数据上训练的模型产生混淆。为了解决这个问题，我们引入了ArEnAV，这是第一个大规模阿拉伯语-英语视听深度伪造数据集，具有话语内语码转换、方言变异和单语阿拉伯语内容。它包含387k个视频和超过765小时的真实和伪造视频。我们的数据集是使用一个集成了四个Text-To-Speech和两个lip-sync模型的新颖管道生成的，能够对多语言多模态深度伪造检测进行全面分析。我们针对现有的单语和多语言数据集、最先进的深度伪造检测模型以及人类评估对我们的数据集进行了基准测试，突出了其推进深度伪造研究的潜力。该数据集可在此处访问。
英文摘要：
Deepfake generation methods are evolving fast, making fake media harder to detect and raising serious societal concerns. Most deepfake detection and dataset creation research focuses on monolingual content, often overlooking the challenges of multilingual and code-switched speech, where multiple languages are mixed within the same discourse. Code-switching, especially between Arabic and English, is common in the Arab world and is widely used in digital communication. This linguistic mixing poses extra challenges for deepfake detection, as it can confuse models trained mostly on monolingual data. To address this, we introduce \textbf{ArEnAV}, the first large-scale Arabic-English audio-visual deepfake dataset featuring intra-utterance code-switching, dialectal variation, and monolingual Arabic content. It \textbf{contains 387k videos and over 765 hours of real and fake videos}. Our dataset is generated using a novel pipeline integrating four Text-To-Speech and two lip-sync models, enabling comprehensive analysis of multilingual multimodal deepfake detection. We benchmark our dataset against existing monolingual and multilingual datasets, state-of-the-art deepfake detection models, and a human evaluation, highlighting its potential to advance deepfake research. The dataset can be accessed \href{https://huggingface.co/datasets/kartik060702/ArEnAV-Full}{here}.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
