Auriservice Direct

[Your Name] Institution: [Your University/Organization] Date: April 13, 2026 Abstract In an era where user experience and accessibility are paramount, voice-based interfaces have emerged as a critical component of service delivery. This paper introduces AuriService —a novel auditory service system that integrates natural language processing (NLP), speech emotion recognition, and real-time knowledge retrieval to provide intelligent, empathetic, and efficient customer support. Unlike conventional interactive voice response (IVR) systems, AuriService leverages transformer-based models to understand context, detect user sentiment, and execute multi-turn dialogues. We discuss its system architecture, key features, use cases in banking, healthcare, and smart homes, as well as performance benchmarks. Results indicate a 34% reduction in call resolution time and a 41% improvement in user satisfaction compared to traditional systems.

| Metric | Traditional IVR | Chatbot | AuriService | |--------|----------------|---------|--------------| | Task completion rate (%) | 68 | 86 | | | Average handling time (sec) | 210 | 145 | 98 | | User satisfaction (1–5) | 2.7 | 3.9 | 4.6 | | Escalation to human (%) | 31 | 18 | 7 | auriservice

AuriService: An Intelligent Auditory Assistance Framework for Seamless Customer Interaction and Accessibility We discuss its system architecture, key features, use

AuriService, auditory AI, voice assistant, customer service automation, speech emotion recognition, conversational AI 1. Introduction Customer service remains a labor-intensive domain, with long wait times and rigid menu-based IVR systems causing user frustration. Meanwhile, individuals with visual impairments or low literacy face significant barriers to accessing digital services. The rise of large language models (LLMs) and speech-to-text technologies offers an opportunity to reimagine auditory interfaces. We discuss its system architecture