we should be able to use this as a vscode extension to solve this issue. is there an sdk to integrate this into electron apps?
We are finalizing an electron app as we speak. That will allow recording anything that runs on your own system
Readit Newssomebee commented on Show HN: Node.js video tutorials where you can edit and run the code · Posted by u/somebee
somebee commented on Show HN: Node.js video tutorials where you can edit and run the code · Posted by u/somebee
Minor issue, Chrome on Windows: cursor position seems to have an offset error -- can never quite get to the end of a line. As you type, text doesn't quite appear where the cursor is.
Will try to push a fix in the next few hours. We are instantiating the monaco editor with a custom font (Source Code Pro) before we're sure the font has loaded, which throws of the char box measurements in monaco. We did have a fix for this in the old (non-backend IDE), so I'll port that over ASAP. Thanks for notifying us :)
somebee commented on Show HN: Node.js video tutorials where you can edit and run the code · Posted by u/somebee
Awesome. But only JS is supported ?
Right now, only js is supported out of the box, but I guess any language that can run via web assembly or other techniques could work. WebContainers has experimental python support, but it won't work with a lot of the dependencies you would usually utilize in python etc.
80x faster than Whisper is an incredible feat. How is Deepgram's transcription accuracy?
Also, have you heard of Conformer-1 by Assembly-AI[1]? It released a few days ago and supposedly scored higher than Whisper on various benchmarks.
In my experience the accuracy is at least a bit better than whisper-small on their enhanced models. But we've just started using it so haven't had time to do many direct comparisons with whisper. Their word-timestamps are _much_ better, which is important if you want to be able to edit the audio based on the transcription.
As for speed I have no idea how they make it so fast, but I'm sure they've written about it somewhere. My guess is at least that they are slicing the audio and parallelising it. Will look into Conformer-1 as well!
I saw deepgrams claims as well an believed them also, then i tried it, it was TERRIBLE. Don't believe them. It only does well on the benchmark they trained it on. It is faster though but the quality is terrible.
Did you try their enhanced models? We're using it for relatively high-quality audio files and their accuracy is better than the whisper small.en model. More importantly, their word level timestamps is worlds better than whisper.
We've been researching different speech models at Scrimba, and went for Whisper on our own infrastructure. A few days ago I stumbled onto Deepgram, which blows whisper out of the water in terms of speed and accuracy (we need high precision word level timestamps). I thought their claim of being 80x faster than whisper had to be hyperbole, but it turned out to be true for us. Would recommend checking it out for anyone who need performant speech-to-text.
> just rerenders on each change
It is known from experience that this approach does not scale beyond toy examples and very simple websites. UX will begin to suffer from render lag somewhere around the UI complexity of an average webstore.
Yes, I've also had this experience with React. I've created several imba apps with more complex UI than an average webstore and still rerender from root without even being close to spending 16ms on a full rerender. It does work. https://www.freecodecamp.org/news/the-virtual-dom-is-slow-me...