Could you explain what you mean the 0.0 case? math.isclose() has an abs_tol parameter for, among other things, handling comparisons to 0.

The Julia equivalent does a good job explaining the 0.0 case: https://docs.julialang.org/en/v1/base/math/#Base.isapprox

I assume “out of the box” is the distinction.

If you're using Python, check out grapheme: https://github.com/alvinlindstam/grapheme

A whole lesson in Unicode in itself right there with your experience, haha!

Fantastic reference. Thanks for sharing!

That's a really good point. I am the author of the article, and this is something I debated during writing. In the end the goal was to provide an "in-depth enough" tutorial on adding speech recognition to an app for people who were new to it and possibly intimidated by the topic. For that, I think SpeechRecognition is a fantastic module.

I had to leave a lot out of this that I wish could have gone in, simply due to length constraints. In that regard, perhaps "The Ultimate Guide to Speech Recognition" wasn't be best choice of title. I'm sure that we'll be updating this article as time goes on, and Google's streaming API is something I want to make sure goes in it.

Also, something that was left out of the article was SpeechRecognition's listen_in_background method, which does solve this problem somewhat. My issue with it is that SpeechRecognition uses a somewhat crude RMS energy based VAD for detecting speech.

Thanks for your feedback!

It may be possible to do this with an LSTD VAD, I always had really good luck with that. I tried a few random ones in here for silence removal - no quality guarantee [0]

I found LTSD pretty robust compared to simpler energy based things as long as you have a small chunk of background sound at the start. The LTSD implementation is largely from my friend Joao, so I can't take credit for the cool part, only the bugs

[0] https://gist.github.com/kastnerkyle/a3661d6be10a0ae9e01fd429...

Cheers! I'll definitely check this out.

For me as a begginer (in speech recognition) this tutorial (and others on RealPython site) are a good start to digg into the topic. That's why I linked it here.

One of the things I like in HNews is that there's often someone who can join discussion and add something to it.

Clearly it's worth to learn and discuss from experience of others to see broader spectrum. Thanks to the author for looking here and dropping few lines.