Emotional Offline Voice Assistant

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License

Introduction

Emotional Offline Voice Assistant is an AI-driven voice assistant capable of understanding and expressing emotions. It can interact with users in a more human-like manner, providing a more engaging and natural user experience. This project is designed to work offline, ensuring user privacy and data security.

Features

• Offline voice recognition and processing for enhanced privacy
• Emotion recognition and expression capabilities
• Natural language understanding for improved user interactions
• Customizable voice and personality
• Cross-platform compatibility

Installation

To install the Emotional Offline Voice Assistant, follow these steps:

1. Clone the repository:

   Now clone this repository and dowload the pretrained speech model.

   git clone https://github.com/TPODAvia/Voice-Assistant
   cd Voice-Assistant
   curl -LJO "https://github.com/TPODAvia/Voice-Assistant/releases/download/v0.0.1-alpha/StyleTTS.zip"
   unzip StyleTTS.zip
   cd ../..

Get the Microsoft Visual Studio:

   cd Voice-Assistant
   python -m venv venv

if strugles of creating venv theen execute this code:

   Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser -Force
   python -m venv venv
   # or
   C:\Users\vboxuser\AppData\Local\Programs\Python\Python311\python.exe -m venv venv

Activate the venv

   ./venv/Script/activate
   # or
   .\venv\Scripts\activate
   # or
   ./venv/Scripts/Activate.ps1

2. Install the required dependencies:

Install torch with cuda https://pytorch.org/get-started/locally/ To test that the cuda is working:

# activate your venv first
cd Voice-Assistant
python docs/cuda_test.py

Install espeak-NG For Windows:

Download and install espeak-ng https://github.com/espeak-ng/espeak-ng

Add to the system variables:

PHONEMIZER_ESPEAK_LIBRARY = C:\Program Files\eSpeak NG\libespeak-ng.dll
PHONEMIZER_ESPEAK_PATH = C:\Program Files\eSpeak NG

For Linux:

   sudo apt-get install libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 python3-tk python3-dev sox python3-pil python3-pil.imagetk espeak -y

Install pip dependencies

   cd Voice-Assistant
   pip install -r requirements.txt

   pip install PyAudio
#    pip install transformers==4.39.0 # new realeases get errors when switching to offline mode
#    pip install openwakeword
#    pip install SoundFile torchaudio munch torch pydub pyyaml librosa git+https://github.com/resemble-ai/monotonic_align.git

3. Configure the voice assistant settings as needed:

   cd /home/vboxuser/Voice-Assistant/Irene-Voice-Assistant/options/core.json
   sudo nano core.json

5. Optionaly, the online voice assistance can be executed in the Voice_assistant_online folder:

   cd Voice_assistant_online
   python voice_assistant_online.py

Usage

To start the Emotional Offline Voice Assistant, run the following command:

cd Voice-Assistant/Irene-Voice-Assistant
python3 runva_neuralnet.py

Once the voice assistant is running, you can interact with it using your microphone or by providing text input.

Perfomance check

To create a profiling image using gprof2dot from the provided script, follow these steps:

1. Profile the Script with cProfile: Modify the script to use the cProfile module to collect profiling data.

2. Run the Script to Generate Profiling Data: Execute the modified script to generate a .prof file containing the profiling data.

3. Convert Profiling Data to a Dot File: Use gprof2dot to convert the .prof file to a .dot file.

4. Generate an Image from the Dot File: Use Graphviz to convert the .dot file to an image format like PNG.

Here is the step-by-step process:

Step 1: Modify the Script to Use cProfile

Add the cProfile module to your script to collect profiling data:

import sys
import cProfile

if __name__ == "__main__":
    profiler = cProfile.Profile()
    profiler.enable()
    main()
    profiler.disable()
    profiler.dump_stats('profile_data.prof')

Step 2: Run the Script

Run the modified script to generate the profile_data.prof file:

python your_script.py

Terminate the script with Ctrl+C after a few seconds to ensure profiling data is collected.

Step 3: Convert Profiling Data to a Dot File

Use gprof2dot to convert the .prof file to a .dot file:

gprof2dot -f pstats profile_data.prof -o profile_data.dot

Step 4: Generate an Image from the Dot File

Use Graphviz to convert the .dot file to an image format like PNG:

dot -Tpng profile_data.dot -o profile_data.png

After these steps, you will have a profile_data.png file that visually represents the profiling data of your script.

Contributing

We welcome contributions to the Emotional Offline Voice Assistant project. If you're interested in contributing, please read our contribution guidelines and code of conduct before getting started.

License

This project is licensed under the MIT License.