Echo.

Echo. is an advanced audio transcription and analysis platform that leverages OpenAI's powerful APIs to provide intelligent insights from audio content. The application offers a seamless interface for uploading or recording audio, generating transcriptions, and analyzing the content through various AI-powered features.

Features

Authentication

• Secure user registration and login system
• Password validation with requirements for length and special characters
• Email format validation
• Session management for authenticated users

Audio Input

• Support for multiple audio file formats (MP3, MP4, MPEG, MPGA, M4A, WAV, WEBM)
• Direct file upload with drag-and-drop functionality
• Real-time voice recording capability
• File size limit of 200MB

AI-Powered Analysis

• High-accuracy audio transcription using OpenAI Whisper
• Automatic summary generation
• Sentiment analysis with detailed reports
• Fact-checking of transcribed content
• Text statistics including word frequency analysis

Interactive Features

• Chat interface for discussing transcriptions
• Previous transcription access and management
• Real-time processing status indicators
• Expandable sections for different types of analysis

Technology Stack

• Frontend: Streamlit
• Backend: Python
• Database: PostgreSQL
• AI Services: OpenAI (GPT-4, Whisper)
• Authentication: Custom implementation with password hashing
• File Storage: Local storage with binary data in PostgreSQL

Installation

1. Clone the repository:

git clone <repository-url>
cd echo

2. Install required packages:

pip install -r requirements.txt

3. Set up your environment variables: Purchase your OpenAI API for using GPT-4 and Whisper Create a .env file in the root directory with:

OPENAI_API_KEY=your_openai_api_key

4. Set up PostgreSQL database:

• Create a database
• Update DB_CONFIG in db_functions.py with your database credentials

5. Run the application:

streamlit run main.py

Usage

1. Authentication

   • Create an account or login with existing credentials
   • Passwords must contain at least 8 characters, including uppercase, lowercase, numbers, and special characters

2. Creating Transcriptions

   • Choose between uploading an audio file or recording your voice
   • Click "Generate Transcript and Summary" to process the audio
   • View the generated transcription, summary, and analysis in the expandable sections

3. Analyzing Results

   • Review the transcription accuracy
   • Read the AI-generated summary
   • Check the sentiment analysis and fact-checking results
   • Explore text statistics and word frequency data

4. Interacting with Transcriptions

   • Use the chat interface to discuss specific parts of the transcription
   • Access previous transcriptions through the "Previous Transcriptions" tab
   • Compare and analyze multiple transcriptions

Database Schema

The application uses the following PostgreSQL tables:

• Users (user_id, email, password)
• Transcripts (transcript_id, file_name, transcription, transcription_summary, sentiment_label, sentiment_report, prev_ai_research, fact_check, user_id)
• AudioFiles (audio_id, file_name, audio_data, transcript_id)
• Messages (message_id, role, message, transcript_id, user_id)

Screenshots#

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Made with ❤️ by Saumya Subham Mishra