The generator first needs a depth map, and then derives the repeating pattern from that. A normal RGB image would be far too noisy; the fine texture variations would break the repetition needed for the brain to fuse the patterns correctly.

Comments URL: https://news.ycombinator.com/item?id=47322333

Points: 3

# Comments: 5

Comments URL: https://news.ycombinator.com/item?id=47163167

Points: 154

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  simedw ~  $ claude -p "random number between 1 and 10" 
  7
  simedw ~  $ claude -p "random number between 1 and 10"
  7
  simedw ~  $ claude -p "random number between 1 and 10"
  7
  simedw ~  $ claude -p "random number between 1 and 10"
  7

I have just added sandhi support, please let me know if it's working better.

The other two are probably things that could be fixed with a bigger and more varied dataset.

I had a quick look at Farsi datasets, and there seem to be a few options. That said, written Farsi doesn’t include short vowels… so can you derive pronunciation from the text using rules?

It's a 9M Conformer-CTC model trained on ~300h (AISHELL + Primewords), quantized to INT8 (11 MB), runs 100% in-browser via ONNX Runtime Web.

Grades per-syllable pronunciation + tones with Viterbi forced alignment.

Try it here: https://simedw.com/projects/ear/

Comments URL: https://news.ycombinator.com/item?id=46832074

Points: 469

# Comments: 153

Comments URL: https://news.ycombinator.com/item?id=46691309

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Since you’ve been so consistent and are using your own software, have you experimented with different resurfacing rates? Did you notice a material difference in recall?

1. How does it know which words I already know? It doesn’t automatically. You provide that set. For example, if you’ve completed HSK 1, you can paste the HSK 1 word list into LangSeed and mark those as "known". From there, new explanations are constrained to that vocabulary. You can also paste in real text and mark the easy words as known, though that’s a bit more manual.

2. How much might I misunderstand word meanings? Depends on how advanced the vocab is and how large your known-word set is. I think of this as building intuition rather than giving dictionary-precise definitions. As you see words in more contexts, that intuition sharpens. This is just my experience from testing it over the last couple of weeks.

3. How inaccurate are the explanations? I tested it on Swedish (my native language). There are occasional awkward or slightly odd phrasings, but it’s rarely outright wrong.