152 karma · joined September 28, 2023
> When I tried to create marketing pages with Starlight in addition to the technical documentation, I nearly gave up. Coming from the Docusaurus world, this wasn't an issue as the starter template comes with a front page and a blog out of the box. You can even create multiple documentations on different paths. We used /docs, for example.
> Starlight, on the other hand, is only built for documentation and not for marketing pages. It even took an ugly hack to make sure the default path is /docs and not /.
> Please don't look at this custom script configured in our astro.config.mjs we need to execute on every page to make sure that the redirection works properly
Love the straight talking. Refreshing in the period of ai slop blogposts
Idea here is this is a unifed TTS wrapper so getVoices is the same for all engines, and bytestream is the same and word events are the same - even if they don't support it we estimate it.
Maybe useful since I see a lot of TTS hackers out there!
NB: I will say JS isnt my bag - so feedback all welcome.
https://audioxpress.com/news/data-over-sound-pioneer-chirp-a...
Update.. as usual I was trying this all day and only after posting this does this work - Here's a bash script https://gist.github.com/willwade/251fa791da27267b5470c75a7b5... - a shortcut for this is way more complicated
Acapela, Nuance - but its around 75 languages.
https://scanningmvp.netlify.app/ - it’s more for my needs of an AT keyboard for scanning than your backlit one but you get the idea.
i probably am not making much sense. Look at where I'm coming from in the world of Assistive Tech - https://docs.acecentre.org.uk/products/echo (go to around 5 min mark in the vide)
Look at PPM. Your prediction model would work better with personalised data. PPM is efficient (nb. I see you are using python - look at this https://github.com/willwade/pylm - although be warned - i think my code is not quite right..)
Layout shifting for finger movement - well its great if you didnt have to look. The time for visual processing the letters adds a significant lag (its why typical word prediction isnt used that much and when it is - not over 3 predictions (I have papers on this if you are interested). But its not all bad..
Switch users who need next letter prediction this could dramatically support their rate of input. (view https://youtu.be/Bhj5vs9P5cw?si=VnytfH_vdEUWuLok&t=73 - now note how the keyboard blocks the scan up. But imagine if it just scanned each letter first by next most likely - or heck - like this repo - actually changes button position and kept the scan pattern the same. It would be a ton more efficient)
(and a bit of a rabbit hole.. What if keys had word predictions on them? This is basically the end result of ACE-LP: https://discovery.dundee.ac.uk/en/publications/ace-lp-augmen...)
from phonemizer.phonemize import phonemize
text = "hello world"
variations = [
phonemize(text, backend="espeak", language="en-us", strip=True),
phonemize(text, backend="espeak", language="en-gb", strip=True),
phonemize(text, backend="espeak", language="en-au", strip=True),
]
I mean, espeak isnt the best but a lot of folks in the ASR/Speech world still are using this right?(NB: If you are on iOS check out the inbuilt one - Settings -> Accessibility -> Spoken Content -> Pronounciations. Adding one it has the ability to phonemize to IPA your spoken message. If someone can tell me where that SDK/API is they use in that I'd love to know) for i, variation in enumerate(variations, 1): print(f"Variation {i}: {variation}")