There’s a difference between speech recognition to keyword recognition.
When we talk about speech, we expect longer sentences and that’s why someone might think about LSTM as there’s a sequence that needs to be take into account.
For keyword detection, since it’s a short sound, a couple of seconds, there’s no need for LSTM, you can just use the spectrogram and an image classifier on it (as shown on the tutorial I posted earlier and this is also the idea behind YAMNet mentioned on the first post).
For speech, maybe this tutorial can help you: https://colab.sandbox.google.com/github/tensorflow/hub/blob/master/examples/colab/wav2vec2_saved_model_finetuning.ipynb 3