# nn-morse

**Repository Path**: cndavy/nn-morse

## Basic Information

- **Project Name**: nn-morse
- **Description**: No description available
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-10-02
- **Last Updated**: 2025-10-02

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Decode morse code using a neural network
Use a neural network to decode morse code! The input is preprocessed by taking the FFT in 20 ms windows. These inputs go into a few dense layers followed by an LSTM. The network does not use time based convolutions on the input, so it can be used in a streaming fashion before all the audio is available.


# Training
Run `./main.py`. Open tensorboard to view progess. The network will converge after a few thousand epochs.

The training uses a realistic morse code generator. It will simulate different speeds, frequency, noise levels and inconsistencies in timing. See `morse.py` for more details.

# Test
Run `./decode_audio.py --model models/001750.pt audio/hello_world.wav`. This will print the prediction, and show a plot of the spectrogram and tokens as predicted by the model.

![](hello_world.png)