Title: What's Not on the Plate? Rethinking Food Computing through Indigenous Indian Datasets Show Chinese title

Title: plate 上没有什么？ 通过土著印度数据集重新思考食品计算

Abstract: This paper presents a multimodal dataset of 1,000 indigenous recipes from remote regions of India, collected through a participatory model involving first-time digital workers from rural areas. The project covers ten endangered language communities in six states. Documented using a dedicated mobile app, the data set includes text, images, and audio, capturing traditional food practices along with their ecological and cultural contexts. This initiative addresses gaps in food computing, such as the lack of culturally inclusive, multimodal, and community-authored data. By documenting food as it is practiced rather than prescribed, this work advances inclusive, ethical, and scalable approaches to AI-driven food systems and opens new directions in cultural AI, public health, and sustainable agriculture. Show Chinese abstract

Abstract: 本文介绍了一个多模态数据集，包含来自印度偏远地区的1000种土著食谱，这些食谱通过一种参与式模式收集，涉及首次参与数字工作的农村工作者。 该项目涵盖了六个州的十个濒危语言群体。 使用专用移动应用程序进行记录，该数据集包括文本、图像和音频，捕捉传统食品实践及其生态和文化背景。 这一举措弥补了食物计算中的空白，例如缺乏文化包容性、多模态和社区创作的数据。 通过记录实际进行的食物实践，而非规定的食物实践，这项工作推进了由人工智能驱动的食物系统的包容性、伦理性和可扩展性方法，并在文化人工智能、公共卫生和可持续农业领域开辟了新方向。