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Where is the boundry then?

You cannot "outsource" the "core"?



I don't know. It's not that it isn't impressive and it is very illustrative of how much you can build, utilizing the tools that are available to all of us. It's just at what point are you writing code and when are you just initializing and configuring an existing tool.

It's also how you present it. If you said: "Building a TensorFlow backed German speech recognition system in only a few hundred lines of code." Then I feel like you're being more honest.


I tried to include TensorFlow in the submission headline, but that would have been too long. "Show HN: State-of-the-Art German Speech Recognition in 284 lines of C++" uses up 72 of the 80 character limit. Originally I also wanted to mention that this is and offline, cloud-free, and privacy-respecting, but that, too, didn't fit.


I can appreciate your dilemma, but I think the submission would have been better served if the title emphasizes the real win, which is improved accuracy over some alternatives (like you mention elsewhere in the comment thread), rather than lines of code (because that invites scrutiny on the wrong, non-salient dimension).


You can do whatever you want. Just don't brag about your line count if all your project does is import dependencies.


It doesn't. It implements a new way of decoding the logits which improves performance by a relative 16% over the previously best German speech recognition, which was Facebook's wav2vec2.

And the size is relevant to people in the industry because DeepSpeech uses 2000+ LOCs for implementing their decoding, so this works better and is 10x less code.


> It implements a new way of decoding the logits which improves performance by a relative 16%

Then you should have mentioned that in the title rather than the LOCs




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