VoiceExpenseTracker v1.0 — Talk. Track. Visualize.

🎙️ VoiceExpenseTracker v1.0 — Talk. Track. Visualize.

A fully voice-enabled expense tracker that listens, understands, saves, and visualizes your spending — all in one click.

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🚀 Overview

VoiceExpenseTracker v1.0 is the first complete public release of a voice-driven expense tracking system built with Python.
You can speak your expenses, and it will automatically parse the amount, category, and date — then store them in a local SQLite database and display live analytics in a beautiful Streamlit dashboard.

All interactions are handled through your voice, including saving, confirmation, and even shutting down the system.

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✨ Key Features

Feature | Description -- | -- 🎙️ Voice-to-Voice Logging | Speak your expenses, and the system replies and confirms through voice 🧠 Smart NLP Parser | Detects amount, category, and date automatically from speech 💾 Local Database | Stores all transactions in voice_expense.db (SQLite) 📊 Interactive Dashboard | Real-time Streamlit charts: bar, pie, and line trend visualizations 🧮 Monthly Rollups | Automatic monthly summaries with category totals 📱 SMS & Gmail Import | Reads payment SMS or emails (Paytm, GPay, etc.) 💬 One-Click Launcher | run_expense_tracker.bat runs backend, dashboard, and voice module together 🔊 Voice-Triggered Exit | Say “stop”, “exit”, or “quit” to close all apps gracefully

🎙️ VoiceExpenseTracker v1.0 — Talk. Track. Visualize.

A fully voice-enabled expense tracker that listens, understands, saves, and visualizes your spending — all in one click.

🚀 Overview

VoiceExpenseTracker v1.0 is the first complete public release of a voice-driven expense tracking system built with Python.
You can speak your expenses, and it will automatically parse the amount, category, and date — then store them in a local SQLite database and display live analytics in a beautiful Streamlit dashboard.

All interactions are handled through your voice, including saving, confirmation, and even shutting down the system.

✨ Key Features
Feature Description
🎙️ Voice-to-Voice Logging Speak your expenses, and the system replies and confirms through voice
🧠 Smart NLP Parser Detects amount, category, and date automatically from speech
💾 Local Database Stores all transactions in voice_expense.db (SQLite)
📊 Interactive Dashboard Real-time Streamlit charts: bar, pie, and line trend visualizations
🧮 Monthly Rollups Automatic monthly summaries with category totals
📱 SMS & Gmail Import Reads payment SMS or emails (Paytm, GPay, etc.)
💬 One-Click Launcher run_expense_tracker.bat runs backend, dashboard, and voice module together
🔊 Voice-Triggered Exit Say “stop”, “exit”, or “quit” to close all apps gracefully
🧩 Tech Stack

Backend: Flask + SQLAlchemy

Voice Engine: SpeechRecognition + gTTS + playsound

Frontend: Streamlit + Plotly

Database: SQLite (auto-generated)

Utils: psutil, python-dotenv, dateparser

⚙️ Installation
pip install -r requirements.txt

🖥️ Run Everything

Option 1️⃣ — One click

run_expense_tracker.bat

Option 2️⃣ — Manual launch

python expensetracker.py --runserver
streamlit run dashboard.py
python expensetracker.py --voice2voice

🗣️ Example Voice Interaction

You: “I spent 500 on groceries yesterday.”
Assistant: “Save ₹500.00 to Groceries for groceries? (y/n)”
You: “Yes.”
Assistant: “Saved successfully.”

You: “Exit.”
Assistant: “Goodbye! Shutting down everything.”

📊 Dashboard Preview

Recent transactions table

Spending by category (bar + pie)

Monthly trend line chart

Rollups table for summaries

Launch at 👉 http://localhost:8501/

🧾 Database Schema
Table Purpose
transactions Stores all expense records
monthly_rollups Cumulative monthly summaries
🧠 Future Roadmap

✅ v1.0 — Complete local voice-based system

⏳ v1.1 — Add Google Sheets sync

⏳ v1.2 — Add mobile companion app (Flutter frontend)

⏳ v2.0 — Add OpenAI LLM for personalized spending advice

💡 Credits

Developed by Mohona Ghosh
KIIT University, Bhubaneswar (2025)
MIT License © 2025

📦 Release Info
Field Value
Tag v1.0
Branch main
Released November 2025
Maintainer Mohona Ghosh
License MIT