/squeak

Squeak: Unleash the power of polyphonic linguistic interaction! Experience a wizardry of speech recognition, blending machine learning magic with real-time translation. Let your whispers compose a symphony of digital dialogue. 🎙️✨

Primary LanguagePythonMIT LicenseMIT

Squeak: The Polyphonic Linguistic Interface

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Welcome to Squeak, where science meets sorcery in the realm of digital linguistics!

GitHub license

Table of Contents

Introduction

Welcome to Squeak, the mystical fusion of data science, linguistics, and code incantations. Squeak is not just another speech recognition application; it's a polyphonic linguistic interface, designed to understand and interact with spoken language. Squeak can transmute your vocal vibrations into tangible expressions of code, making the digital world respond to your every utterance.

Squeak in Action

Installation

To summon the power of Squeak on your local environment, follow these mystical incantations:

  1. Clone this repository:

    git clone https://github.com/alpha2lucifer/squeak.git

  2. Navigate to the project directory:

    cd squeak

  3. Create a virtual environment:

    python -m venv venv

  4. Activate the virtual environment:

    • For Windows:

      .\venv\Scripts\activate

    • For macOS and Linux:

      source venv/bin/activate

  5. Install project dependencies:

    pip install -r requirements.txt

Getting Started

To unleash Squeak's magic, run the following command:

python manage.py runserver

Now, open your preferred browser and visit http://127.0.0.1:8000/. Click the "Click to Speak" button and witness your words being transformed into code runes.

Technology Behind

Squeak is powered by a symphony of modern technologies, including:

  • Django: The enchanting web framework that orchestrates the entire performance.
  • JavaScript: The mystical language that connects your incantations to the digital realm.
  • Web Speech API: An arcane API for capturing your vocal vibrations.
  • HTML/CSS: The visual spells that render the incantation results on your screen.

Data Science Magic

Beneath the surface, Squeak employs data science to unravel the mysteries of spoken language. Data science techniques are used for:

  • Speech Recognition: A complex blend of machine learning models that deciphers your words.
  • Language Processing: NLP and sentiment analysis to understand context and emotions. (future updates)
  • Real-time Interaction: Algorithms that make your words trigger actions and responses. (future updates)

The webkitSpeechRecognition interface, part of the Web Speech API, enables speech recognition capabilities within web browsers that support it. It is specifically used for implementing speech recognition functionality in web applications. Here's an explanation of the technology behind webkitSpeechRecognition:

  1. Web Speech API: The Web Speech API is a JavaScript API that enables developers to incorporate speech recognition and synthesis capabilities into web applications. It consists of two main components: speech recognition and speech synthesis. The webkitSpeechRecognition interface is the part of the API responsible for speech recognition.

  2. Browser Support: As the name suggests, webkitSpeechRecognition originated in the WebKit rendering engine, which powered browsers such as Google Chrome and Safari. However, its support has expanded to other modern browsers that implement the necessary features for speech recognition.

  3. Speech Recognition Configuration: With webkitSpeechRecognition, developers can configure various properties to control the behavior of the speech recognition process. These properties include settings for language, continuous recognition, and interim results, allowing developers to customize how the API handles speech input.

  4. Event-Driven Model: webkitSpeechRecognition follows an event-driven model, where developers can define event handlers for different stages of the speech recognition process. Events such as onstart, onresult, and onerror provide developers with hooks to handle different stages of the speech recognition process, such as starting recognition, processing results, and handling errors.

  5. Language Support: The interface allows developers to specify the language for speech recognition, making it possible to recognize and transcribe speech in various languages. Developers can set the language property to the appropriate language code to enable speech recognition for specific languages.

  6. Real-time Speech Recognition: webkitSpeechRecognition facilitates real-time speech recognition, enabling developers to capture spoken input and process it dynamically within the web application. This allows for immediate feedback and response based on the recognized speech input, making it suitable for interactive applications.

  7. Integration with JavaScript: The webkitSpeechRecognition interface seamlessly integrates with JavaScript, allowing developers to easily incorporate speech recognition functionality into their web applications without the need for complex plugins or external software.

Overall, webkitSpeechRecognition simplifies the integration of speech recognition capabilities into web applications, providing developers with a convenient and accessible tool for implementing speech-based interactions and functionalities directly within the web browser environment.

Contributing

You are invited to join the Squeak coven. Contribute your code spells, enhance our linguistic database, and help us uncover new realms of possibility. Check out our Contribution Guidelines for more information.

License

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

Feel the magic, let your voice be heard, and explore the wonders of Squeak! 🌌✨