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Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox. It also generates a suggested response using OpenAI's GPT-3.5 for the user to say based on the live transcription of the conversation.

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🎧 Ecoute

Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox. It also generates a suggested response using OpenAI's GPT-3.5 for the user to say based on the live transcription of the conversation.

📖 Demo

demo.mp4

Ecoute is designed to help users in their conversations by providing live transcriptions and generating contextually relevant responses. By leveraging the power of OpenAI's GPT-3.5, Ecoute aims to make communication more efficient and enjoyable.

🚀 Getting Started

Follow these steps to set up and run Ecoute on your local machine.

📋 Prerequisites

  • Python 3.x
  • An OpenAI API key
  • Windows OS (Not tested on others)
  • FFmpeg

If FFmpeg is not installed in your system, you can follow the steps below to install it.

First, you need to install Chocolatey, a package manager for Windows. Open your PowerShell as Administrator and run the following command:

Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))

Once Chocolatey is installed, you can install FFmpeg by running the following command in your PowerShell:

choco install ffmpeg-full

Please ensure that you run these commands in a PowerShell window with administrator privileges. If you face any issues during the installation, you can visit the official Chocolatey and FFmpeg websites for troubleshooting.

🔧 Installation

  1. Clone the repository:

    git clone https://github.com/SevaSk/ecoute
    
  2. Navigate to the ecoute folder:

    cd ecoute
    
  3. Install the required packages:

    pip install -r requirements.txt
    
  4. Create a keys.py file in the ecoute directory and add your OpenAI API key:

    echo 'OPENAI_API_KEY = "API KEY"' > keys.py
    

    Replace API KEY with your actual OpenAI API key.

🎬 Running Ecoute

Run the main script:

python main.py

Now, Ecoute will start transcribing your microphone input and speaker output in real-time, and provide a suggested response based on the conversation. It may take a couple of seconds to warm up before the transcription becomes real-time.

⚠️ Limitations

While Ecoute provides real-time transcription and response suggestions, there are several known limitations to its functionality that you should be aware of:

Default Mic and Speaker: Ecoute is currently configured to listen only to the default microphone and speaker set in your system. It will not detect sound from other devices or systems. If you wish to use a different mic or speaker, you will need to set it as your default device in your system settings.

Whisper Model: We utilize the 'tiny' version of the Whisper ASR model, due to its low resource consumption and fast response times. However, this model may not be as accurate as the larger models in transcribing certain types of speech, including accents or uncommon words.

Language: The Whisper model used in Ecoute is set to English. As a result, it may not accurately transcribe non-English languages or dialects. We are actively working to add multi-language support to future versions of the program.

📖 License

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

🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests to improve Ecoute.

About

Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox. It also generates a suggested response using OpenAI's GPT-3.5 for the user to say based on the live transcription of the conversation.

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