Dialect Identification of Gondar, Gojjami, and Showa Language of Amharic Using AI and NLP

Artificial intelligence (AI) for dialect identification in Amharic is specifically targeting the Gondar, Gojjami, and Showa dialects. By using AI techniques, including machine learning and natural language processing (NLP), our study aims to develop a model capable of automatically identifying and distinguishing between these Amharic dialects. A diverse dataset comprising samples from each variety is utilized to extract linguistic features, encompassing phonetic characteristics, syntactic patterns, and unique word usage. The model is trained using AI algorithms such as support vector machines, decision trees, random forests, or neural networks, and fine-tuned for enhanced accuracy and generalization. Our research endeavors to contribute to the preservation and recognition of linguistic diversity within the Amharic language. By deploying this AI model, linguists, language enthusiasts, and communities can effectively identify and appreciate the nuances of the Gondar, Gojjami, and Showa dialects, promoting cultural heritage and fostering inclusivity. This study exemplifies the power of AI in dialect identification, emphasizing its potential to safeguard and celebrate the diverse Amharic dialects.