Hotword Detection with Porcupine and Python
Project description
Hotword Detection
Overview
In the realm of modern technology, voice-controlled applications have emerged as an integral component of our digital landscape. Propelled by the widespread adoption of virtual assistants such as Jarvis, Siri, and Alexa, users have become accustomed to seamless interactions with their devices through spoken commands. At the core of these sophisticated applications lies a critical functionality — Hotword detection. This essential feature serves as the catalyst, prompting the system to actively listen and respond, creating a dynamic and intuitive user experience.
This Python module provides a lightweight and efficient solution for implementing hotword detection using the Porcupine library developed by Picovoice. Designed for real-time performance, this module enables developers to easily integrate voice-triggered commands into their applications, enhancing user engagement and accessibility.
Key Features
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Real-time Hotword Detection: Detect predefined hotwords with minimal latency.
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Customizable Keywords: Easily modify the list of hotwords based on application requirements.
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Cross-Platform Compatibility: Works seamlessly on various platforms, including Windows, macOS, and Linux.
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User-Friendly API: Simple functions for easy integration into existing projects.
Installation
You can install the Hotword Detection module via PyPI:
pip install pico_hw_detection
Usage
To utilize the hotword detection capabilities, you can use the following code:
from hotword_detector import hotword_detection
# Replace 'your_access_key' with your actual Picovoice access key.
hotword_detection('your_access_key')
This will initiate the listening process, and you will receive notifications in the console whenever a hotword is detected.
Technical Details
The core functionality is encapsulated in the hotword_detection function, which leverages the Picovoice Porcupine API. The function initializes the Porcupine engine, listens for audio input, and processes it to detect specified hotwords.
Contribution
Contributions are welcome! If you encounter any issues or have suggestions for enhancements, feel free to open an issue or submit a pull request.
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