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@article{175117,
        author = {Habtamu Weldemikael Gebre and Deborah Ketema Ambelo and Rufeyda Abdusemed Hassen and Isaac Francis Pamba and Dr.Rajinikanta Mohantty},
        title = {Developing a Virtual Personal Assistant for Amharic and Swahili Using NLP and Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2548-2555},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175117},
        abstract = {This project develops a virtual personal assistant for underrepresented African languages, starting with Amharic and Swahili, using advanced Natural Language Processing (NLP) and Machine Learning techniques. Key objectives include collecting linguistic data, fine-tuning language models, and creating a culturally appropriate user interface. Core functionalities, such as translation and task assistance, are built on robust language understanding systems, leveraging transfer learning and data augmentation to overcome resource scarcity. User-centric design ensures accessibility and cultural sensitivity, with iterative testing for refinement. This initiative addresses the challenges of limited linguistic resources, aiming to enhance digital inclusivity and serve as a foundation for supporting other low-resource languages.},
        keywords = {Virtual Assistant, Amharic, Swahili, Natural Language Processing, Machine Learning, Low-Resource Languages, Cultural Sensitivity},
        month = {April},
        }