The Role of Natural Language Processing in Addressing the Everyday Challenges Faced by Local Vendors in India

This study investigates the everyday challenges faced by local vendors and street sellers in India, with a focus on language barriers, digital payment adoption, multilingual customer communication, and limited digital literacy. India's informal economy comprises an estimated 63 million micro-enterprises that remain largely excluded from the opportunities created by the Digital India programme and the Unified Payments Interface (UPI) ecosystem. Using a convergent mixed-methods research design, this paper combines a structured survey of 320 vendors across Delhi, Jaipur, Pune, and Coimbatore with 48 in-depth interviews and secondary data analysis. Findings reveal that 74% of vendors identify language as their primary barrier to digital adoption, and only 31% could complete a digital transaction independently at first contact. The paper proposes VendorVaani, an integrated Natural Language Processing (NLP) framework incorporating voice-based UPI navigation, multilingual chatbot assistance, and speech-to-text inventory management, designed specifically for low-literacy users in Indian regional language settings. Technologies evaluated include IndicBERT, MuRIL, IndicWav2Vec, and OpenAI Whisper for Indian language speech recognition. This research contributes to the fields of computational linguistics, digital financial inclusion, and human-computer interaction, with direct implications for policy design under the Digital India initiative.