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Vedant Jagtap
Vedant Jagtap

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Building a Voice-Controlled AI Agent with Whisper and Streamlit

#machinelearning #webdev #ai #python

🚀 Introduction

In this project, I built a voice-controlled AI agent that processes audio input, converts it into text, detects user intent, and performs actions such as file creation, code generation, summarization, and chat.

🧠 System Architecture

The system follows a simple pipeline:

Audio Input → Speech-to-Text → Intent Detection → Action Execution → UI Output

🔊 Speech-to-Text

I used OpenAI Whisper (local model) to convert audio into text. Whisper provides high accuracy even with different accents and noise.

🤖 Intent Detection

The system analyzes the transcribed text and classifies it into:

  • Create File
  • Write Code
  • Summarize Text
  • General Chat

⚙️ Actions
Based on the detected intent, the system performs:

  • File creation inside a safe output directory
  • Code generation and saving into files
  • Text summarization
  • Chat responses

💻 User Interface

I used Streamlit to build a simple and interactive UI that displays:

  • Transcribed text
  • Detected intent
  • Action results

⚡ Challenges Faced

  • Handling speech recognition errors
  • Managing file safety using a restricted output directory
  • Designing a clean UI pipeline

🎯 Conclusion

This project demonstrates how to build a local AI agent that integrates speech processing, NLP, and automation into a single system.

🔗 Links

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