Stages and Methods of Data Collection for Developing an Artificial Intelligence Model for Recognizing Letters of the Karakalpak Sign Language

This article delves into the comprehensive process of data collection necessary for the development of an effective artificial intelligence model proficient in recognizing gestures within the Karakalpak language. The authors meticulously explore various stages of data collection, encompassing the meticulous selection and preparation of training datasets, the innovative development of methods for capturing and meticulously recording gestures, alongside the intricate processing of the amassed data. Furthermore, the article thoroughly discusses the fundamental principles and advanced approaches involved in crafting a reliable and precise AI model tailored specifically for gesture recognition within the Karakalpak language, thus potentially catalyzing significant advancements in computer vision and natural language processing systems tailored for this linguistic community. This research not only contributes to the field of AI but also holds promise for enhancing communication technologies and facilitating inclusivity for the Karakalpak-speaking population. By shedding light on the challenges and opportunities in gesture recognition within this linguistic context, the study paves the way for future innovations in AI-driven language understanding and human-computer interaction.