A demonstration version of the "Harmony" algorithm - an innovative solution for audio signal processing using Convolutional Neural Networks (CNN).
This project was created as part of the OPEN DEEP WATER initiative and demonstrates practical applications of modern machine learning methods for audio data analysis and processing.
- Audio signal processing using CNN
- Demonstration of the "Harmony" algorithm
- Examples of practical neural network approaches implementation
The project is designed to demonstrate the potential and effectiveness of applying convolutional neural networks in the field of audio processing, showcasing promising directions for the development of machine learning technologies in audio analytics.
The demo works on Linux systems but can be implemented on any platform, including embedded systems.
./harmony_encoder -t "HELLO WORLD"./harmony_decoder audio_samples/harmony_encoded.wav --tensorflow --model exported_model/- Primary support: Linux
- Cross-platform: Can be adapted for Windows, macOS, and embedded systems
- Embedded systems: Compatible with various embedded platforms
PS: This small project was created to demonstrate CNN capabilities on various platforms. The system represents an underwater communication solution for receiving and transmitting text messages, showcasing the practical application of neural networks in challenging acoustic environments.
Project developed as part of OPEN DEEP WATER