阿布扎比技术创新研究所（TII）是一家国有研究机构，近日发布了经阿联酋阿拉伯语方言训练的AI模型，旨在提升翻译、转录及语音服务能力。Falcon-Emirati模型及其相关的语音识别和图像/文档文字提取工具体积相对较小。据TII称，该语音识别模型拥有16亿个参数，但其准确性超过了拥有300亿个参数的模型。
Abu Dhabi’s Technology Innovation Institute, a state-run research body, released AI models trained on the Emirati Arabic dialect, improving translation, transcription, and voice-enabled services. The Falcon-Emirati model and related tools for speech recognition and extracting Arabic text from images and documents are relatively compact. The speech recognition model has 1.6 billion parameters, but is more accurate than a 30-billion-parameter model, according to TII.
阿拉伯语的AI训练一直落后于其他语言，部分原因是方言差异巨大，且对于仅掌握新闻和教科书中正式阿拉伯语的人来说，这些方言往往难以理解。这导致一些机器翻译出现滑稽的错误，有时甚至将无害的词汇翻译成英语中的粗俗用语。TII旨在通过利用当地方言、习语和文化参考来训练模型，从而消除这些错误，并最终使AI在该地区发挥更大的作用。—— Mohammed Sergie
AI training in Arabic has lagged behind other languages, partly because dialects vary widely and can be incomprehensible to people who know only the formal Arabic used in news reports and textbooks. This has made some machine translations comically inaccurate, sometimes turning innocuous words into vulgar references in English. TII aims to eliminate those errors by training models on local dialects, idioms, and cultural references, ultimately making AI more useful in the region. — Mohammed Sergie