Real-time ambient sound and wake word detection
Project description
Oremi Ohunerin
Oremi Ohunerin serves as the real-time audio detection component of the Oremi Personal Assistant project. It operates as a high-performance WebSocket server capable of concurrently identifying environmental sounds and detecting specific wake words.
Leveraging cutting-edge technologies like TensorFlow YAMNet for comprehensive environmental sound classification and PocketSphinx for precise, localized wake word identification, Ohunerin ensures highly accurate recognition of acoustic events.
Documentation
All project documentation—including features, deployment steps, the audio detection WebSocket protocol details and the complete API Reference can be found at: https://demsking.gitlab.io/oremi-ohunerin
License
Licensed under the Apache License, Version 2.0.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file oremi_ohunerin-4.0.0b2-py3-none-any.whl.
File metadata
- Download URL: oremi_ohunerin-4.0.0b2-py3-none-any.whl
- Upload date:
- Size: 14.3 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0ac1c9988c09763a1b91db613ef5952031bbba2b61bf9df85cd5f8d7b052a6dc
|
|
| MD5 |
d0dade1c238985874709499389b9b99a
|
|
| BLAKE2b-256 |
ca40134a228f6ce9ddca5df49d6b44e3ef8b4c1f12c6d918c52b7bdb2889183f
|
