1-800-BAD-CODE / morsecode_en_quartznet_10x5

huggingface.co
Total runs: 10
24-hour runs: -1
7-day runs: 0
30-day runs: -11
Model's Last Updated: August 06 2022

Introduction of morsecode_en_quartznet_10x5

Model Details of morsecode_en_quartznet_10x5

Model Overview

This model is a Morse Code recognition model. It was trained with the package at https://github.com/1-800-BAD-CODE/MorseCodeToolkit .

This model accepts as input audio signals sampled at 8khz containing Morse code. The model produces the English transcription of the Morse code signal.

For inference, only the base NeMo package needs to be installed because this is just an ASR model trained to decode Morse code signals rather than speech signals.

How to Use this Model

With NeMo is installed, this model can be used to run inference on Morse code audio files.

Automatically instantiate the model
import nemo.collections.asr as nemo_asr

asr_model = nemo_asr.models.ASRModel.from_pretrained("1-800-BAD-CODE/morsecode_en_quartznet_10x5")
Transcribing using Python

First, let's download an example Morse code audio file from Wikipedia:

wget https://upload.wikimedia.org/wikipedia/commons/0/04/Wikipedia-Morse.ogg

Then simply do:

asr_model.transcribe(['Wikipedia-Morse.ogg'])
['WELCOME TO WIKIPEDIA, THE FREE ENCYCLOPEDIA THAT ANYONE CAN EDIT.']
Limitations

This model was trained on synthetic Morse code data generated by https://github.com/1-800-BAD-CODE/MorseCodeToolkit . Any Morse code generated with parameters outside of the range of the parameters used to generate the training data will not be well recognized by the model.

Runs of 1-800-BAD-CODE morsecode_en_quartznet_10x5 on huggingface.co

10
Total runs
-1
24-hour runs
-1
3-day runs
0
7-day runs
-11
30-day runs

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