Telugu Conversational Intelligent Farming Assis-tant with Machine Learning-Based Crop Recommendation and Voice Interaction
Authors-B.Beulah, Sandhya Rani
Keyword-Agricultural Voice Assistant, Crop Recommendation System, Random Forest, Machine Learn-ing, Natural Language Processing, Speech Recognition, Google Text-to-Speech, Telugu Lan-guage Processing, Smart Agriculture, Precision Farming.
The agriculture sector is increasingly adopting intelligent technologies to improve farming effi-ciency and decision-making. Farmers in rural regions often encounter difficulties in accessing modern agricultural advisory systems because many available applications rely on text-based interfaces and are developed primarily in English. To overcome these limitations, this research proposes a Telugu-enabled intelligent farming assistant that combines voice interaction with machine learning-based crop recommendation. The proposed framework allows farmers to communicate naturally through speech and receive instant responses in Telugu. Speech recogni-tion techniques convert spoken queries into text, while Natural Language Processing interprets the user's request and retrieves appropriate agricultural information. For crop recommendation, the system employs the Random Forest machine learning algorithm using environmental pa-rameters such as soil pH, rainfall, humidity, and temperature. Google Text-to-Speech technology transforms the generated response into natural Telugu speech, making the application suitable for farmers with limited literacy or technical knowledge. If the requested information is unavailable in the local knowledge repository, the system retrieves relevant agricultural content from online resources to provide comprehensive assistance. The integrated solution improves accessibility to agricultural information, supports informed crop selection, and promotes sustainable farming practices. The proposed system demonstrates that combining machine learning, voice technolo-gy, and regional language support creates a practical digital assistant capable of enhancing agri-cultural productivity while simplifying technology adoption among Telugu-speaking farmers
Doi-[https://doi.org/10.5281/zenodo.21735338]