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Nectar Speech-to-Text And Text-to-Speech Engine

Project description

🍯 NectarSTT

Nectar Speech-to-Text Engine

NectarSTT (Nectar Speech To Text) is a Python-based speech recognition engine designed for real-time, offline-capable voice input. It is built to be modular, extensible, and suitable for AI assistants, automation systems, and accessibility tools.

This project focuses on accurate speech recognition, low latency, and tight integration with AI pipelines.


✨ Features

  • 🎙️ Real-time speech-to-text
  • 🧠 Modular engine design (easy to extend)
  • ⚡ Optimized for low latency
  • 🔌 Designed to integrate with AI / assistant systems
  • 🖥️ Cross-platform (Windows, Linux)
  • 🧩 Compatible with TTS pipelines (Piper / eSpeak NG)

🛠️ Installation

0️⃣ Direct install

pip install nectarstt
  • OR if you want code

1️⃣ Clone the repository

git clone https://github.com/headlessripper/NectarSTT.git
cd NectarSTT

2️⃣ Create a virtual environment (recommended)

python -m venv venv venv\Scripts\activate

3️⃣ Install dependencies

pip install -r requirements.txt


📁 Usage Examples

Direct use after installation

  • to use the GUI for NectarSTT run:
    NectarSTT
    

  • use in code:

TTS:

from nectarstt import piper_tts

piper_tts("This is top-level API usage.", "out.wav")

STT:

from nectarstt import record_until_silence

text = record_until_silence()

⚠️ Note: Before you use download the Main-Engine from Engine then extract it to the root folder of your project.


📦 Models & Assets

Due to GitHub size limits, speech models and voice data are zipped into Main-Engine.zip.
This archive contains:

  • Main-Engine/Model/
  • Main-Engine/TTS-Engine/
  • Main-Engine/STT-Engine/
  • Main-Engine/Images/
  • Main-Engine/Sound/
  • Main-Engine/Source/

Extract Main-Engine.zip into the project directory before running NectarSTT.

💡 A setup script or model downloader may be added in future releases.


🚀 Roadmap / Ideas

  • Automated model download & setup script
  • Extended TTS engine support
  • Additional language models
  • Optional Futher GPU acceleration (where supported)
  • Enhanced logging and debugging tools

🤝 Contributing

Contributions are welcome!

You can:

  • 🐛 Report bugs
  • 💡 Suggest new features
  • 🔧 Submit pull requests

Please open an issue to discuss major changes before starting work.


📜 License

Use a Custom License

⭐ Support

If you find NectarSTT useful:

  • ⭐ Star the repository
  • 🐞 Report issues
  • 💬 Share feedback and ideas

Built with ❤️ in Python for high-quality, low-latency STT And TTS Engine

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