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Cover image for Built an AI-powered voice receptionist
Built an AI-powered voice receptionist system capable of handling real-time phone conversations, answering customer questions, and assisting with appointment booking workflows. The system combines speech-to-text, large language models, and text-to-speech technologies to create natural voice interactions over phone calls. Key contributions: • Built a real-time voice conversation workflow for handling inbound customer calls • Integrated speech-to-text processing for live voice transcription • Used AI language models to generate context-aware conversational responses • Implemented text-to-speech voice generation for natural AI responses during calls • Developed multi-turn conversation flows for collecting customer information and appointment details • Built backend logic to manage conversation state and call workflows • Worked on browser-based softphone integration for handling calls through the web Tech stack: • Python • Flask • Twilio • Whisper • Groq / Llama 3 • ElevenLabs / Edge-TTS • AI Conversation Systems • Voice Automation This project strengthened my experience in voice AI systems, conversational workflows, speech processing, and real-time automation for customer communication.
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