Voice-Based Email System: Simplifying Email Communication with Speech Recognition

Overview

The Voice-Based Email System is a Python-powered application that enables users to send and read emails using voice commands. By integrating speech recognition, text-to-speech synthesis, and email handling, this system enhances accessibility, making email management more intuitive, especially for visually impaired users or those who prefer hands-free interaction.

Key Features

Implementation Demo

Watch how the user can send the mail:

Watch how the system reads the recent mails from an individual:

Source Code

Explore the complete source code of the Voice-Based Email System on GitHub:

View Source Code on GitHub

System Design & Implementation Approach

1. Seamless Voice-Based User Interaction

- Uses SpeechRecognition for transcribing user commands into text.

- Implements pyttsx3 for converting system responses into speech.

- Users follow a guided workflow to either send or read emails, with prompts ensuring clarity.

2. Efficient Email Handling

- Sending Emails: Captures recipient names, subject lines, and message content, then sends via yagmail.

- Reading Emails: Connects to Gmail IMAP, retrieves messages, and reads them aloud.

3. Adaptive Speech Recognition & Noise Handling

- Implements ambient noise adjustment for improved recognition.

- Uses multiple speech recognition attempts to minimize errors.

- Provides real-time feedback and re-prompts if recognition fails.

Technical Learnings & Challenges

1. Working with Speech Recognition APIs

- Implemented Google Speech-to-Text API for accurate voice transcription.

- Handled speech errors and misinterpretations using exception handling.

- Adjusted for different speech patterns and accents.

2. Email Automation & Security

- Integrated IMAP and SMTP protocols for reading and sending emails.

- Managed OAuth-based authentication alternatives for security.

3. Improving User Experience Through AI Assistance

- Developed an interactive flow where the system asks questions based on user intent.

- Implemented conditional decision-making to handle different user inputs dynamically.

4. Handling Real-Time Voice Inputs

- Optimized microphone usage to minimize recognition delays.

- Implemented background noise suppression for cleaner input processing.