Get your speech commands recognition model in 10 minutes
| Step 1: determine up to 5 speech commands to be recognized. |
| Step 2: add 20 1-second audio samples for each speech command, and label them. |
| Step 3: train the model, and check training accuracy. |
| Step 4: add audio samples, and check predictions. |
| Step 5: re-train the model with more audio samples. |
| Step 6: download speech_model.py, and upload it to your M5StickS3 with the IDE (needs the speech firmware). |
| 💡 Tip: over 100 audio samples are needed to train a decent model. |
| 💡 Tip: a low training accuracy indicates audio samples are of bad quality or mis-labelled. |
| 💡 Tip: be prepared when clicking Add Audio Sample button, you have 1 second to say the speech command. |
Model training is based on TensorFlow.js in browser. You audio samples are not saved to any server.
| Creation Time | Audio Sample | Wave | Spectrogram | Speech Command | Prediction | Probability | Quantized Prediction | Quantized Probability |
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