221–230 of 251 posts
> The result, up front It's very welcome, to start with this. However, just from this heading, I knew with 90% certainty that the post was AI generated.
I wonder if I would have less of an issue with this if such blog posts would just start with: “I asked $model $model-version the following: $prompt. Here is what I got.”
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Recently contributed a patch to FluidAudio that sped up Parakeet V2 and V3 to 320x and 282x faster than real time, respectively: https://github.com/FluidInference/FluidAudio/pull/507 That means one hour of audio transcribed in 11.25 and 12.75 seconds. The Inscribe post doesn't give a speed factor for SpeechAnalyzer. However, this Argmax blog post reports 70: https://www.argmaxinc.com/blog/apple-and-argmax Based on th…
The difference using an mp3 seems to be smaller: yap seems to use about the same time but fluidaudio seems to take twice as long. Do you happen to know why?
https://github.com/FluidInference/FluidAudio/pull/799
With the updated PR code, ran a test comparing transcribing (using Parakeet V3) a 1 hr stereo 44.1 kHz mp3 vs the same audio in 16 kHz mono wav format. The result was about 21.3% slower with the mp3 vs the wav, i.e. that's the overhead of decoding + resampling.
Currently the decoding + resampling is done up front. If it was done in a pipelined fashion with the inference, that overhead can be eliminated. This is what I did in a recent app I made:
https://apps.apple.com/us/app/drea-podcast-ad-blocker/id6759...
It uses FluidAudio as well, but I forked it and replaced the audio decoding code to (a) use mpg123 instead of the native Apple API and (b) do audio decoding and inference in a pipelined fashion. These two changes effectively eliminated the overhead. mpg123 is quite a bit faster than the native Apple API at mp3 decoding (has some very optimized arm64 assembly routines), and the pipelining ensures that the inference is never starved by the mp3 decoding.
Contributing this pipelined setup to FluidAudio would be good.
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I think that's parakeet doing its job there. That is a closer reflection of what you've actually said. The trick is then throwing that output through some additional deterministic and non-deterministic steps to tidy it up however you prefer. It's exactly what I do with my free and open source dictation app (dictator.robgough.net) for Mac+iOS. And of course, everything stays entirely on-device. Gemma E4B is really won…
Oh yeah, this one’s worth hyperlinking https://dictator.robgough.net Great work Rob! Indeed private as promised per App Privacy Report, “Domains contacted directly by app”: cas-bridge.xethub.hf.co; huggingface.co; mzstorekit.itunes.apple.com Site could identify our device and send iOS visitors to the iOS page (or maybe that’s against the vibe and we should tap it ourselves). App might be able to launch the keyboard s…
I really wanted to have background audio and make it so the keyboard would directly record audio etc, but my first pass didn't make it through app review (and that was just keeping background audio listening AFTER you'd already started a recording). I could maybe have fought it, but figured if I was already butting up against app review there was little point as they'd likely reject in a future release anyway.
Re: analytics, It is quite weird having no idea how many people are using the app. It does leave you a little blind, but I figure people will get in touch if they have big enough problems with it.
For the Google app, I believe Gemma E2B and E4B both have audio input, so I suspect they're using one of those.
Whisper is the wrong model to benchmark against, or rather, there are better models that are state of the art now like Nemotron and Parakeet both by Nvidia, as well as Mistral's Voxtral and Cohere Transcribe. However, what's funny is, RIP to a lot of the paid apps that simply wrap Whisper, I'm sure Apple will make a native GUI such as a recorder app for macOS that obviates the need for these wrappers, which everyone…
I'd love this, but updated spotlight did not obviate my need for Raycast. I question Apple's ability to make good software at this point.
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I use Systran/faster-whisper-medium for real-time subtitling, but you need to get used to the context it's used it and the weirdness it translates into. Parakeet has great mandarin>CN text, but running that + a translation model has been tricky and I never got it fast.
Thank you for this too. I am running in an offline scope so I don't need speed just quality. I'm willing to do it overnight as well if required.
I use TranscriptionSuite, which is focused on offline transcription, and supports Parakeet as well as whisper and others (https://github.com/homelab-00/TranscriptionSuite) The dev was sweet enough to improve the live mode GUI so that I and some friends can use it when playing on Chinese mmo servers.
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> RIP to a lot of the paid apps that simply wrap Whisper I started using a few open source apps for transcription and eventually subscribed to a paid one... On paper, it's not hard to compete, but for this use case, a few rough edges make it really frustrating to use. Like a keyboard that sometimes doubles the letter "e" Automatic dictionary, seamless language switch, no issues with accents, etc... Putting the effort…
I built my own because I was frustrated with a lot of the free options. Largely because a lot of them had an upsell to be able to do the secondary post-processing step with an LLM. And it wouldn't pick up things like emojis properly or say numbers. Because of that, I left quite a lot of options in there for customising and adding additional steps, etc. Feel free to take a look: dictator.robgough.net My initial Mac ve…
> unfortuntately parakeet-v3 model doesn;t recieve or output language id https://github.com/NVIDIA-NeMo/Speech/issues/14799#issuecomm...
Also this:
> If you are using Parakeet for English only then you should be using V2. V3 is for several languages and is worse at English only. https://news.ycombinator.com/item?id=48897908
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As a Texan first, American second, I sympathize with this statement. Siri can't understand me probably 25% of the time. I use STT for iMessage while in the car, and half the time it will take 3+ times to either get it right or me give up, and hope to remember to text them by hand when I next stop.
What does this mean? When I pledged my oath to become a citizen, I had to promise to put America above all other allegiances. Is it in relation to allegiance in the general sense or some weird statement that only relates to STT?
Whisper is the wrong model to benchmark against, or rather, there are better models that are state of the art now like Nemotron and Parakeet both by Nvidia, as well as Mistral's Voxtral and Cohere Transcribe. However, what's funny is, RIP to a lot of the paid apps that simply wrap Whisper, I'm sure Apple will make a native GUI such as a recorder app for macOS that obviates the need for these wrappers, which everyone…