Building an end-to-end Speech Recognition model in PyTorch
This seems to be a CTC model. CTC is not really the best option for a good end-to-end system. Encoder-decoder-attention models or RNN-T models are both better alternatives.<p>There is also not really a problem about available open source code. There are countless of open source projects which already have that mostly ready to use, for all the common DL frameworks, like TF, PyTorch, Jax, MXNet, whatever. For anyone with a bit of ML experience, this should really not be too hard to setup.<p>But then to get good performance, on your own dataset, what you really need is experience. Probably taking some existing pipeline will get you some model, with an okish word-error-rate. But then you should tune it. In any case, even without tuning, probably encoder-decoder-attention models will perform better than CTC models.