[0] https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize
[1] https://huggingface.co/spaces/OpenMOSS-Team/MOSS-transcribe-...
Is parakeet state of the art? It always transcribes speech fragments for me, like if I stutter and say "m-m-m-map" parakeet will dutifully transcribe "m m m map". Which I guess could be a good thing or a bad thing depending on what you want. Whisper does not do that however.
I do like cohere transcribe a lot.
Apparently MOSS-Transcribe-Diarize is quite good too as it released only a few days ago.
With whisper v3 turbo, I can almost always live with the few mistakes because the overall stream-of-thought word-salad I provide is still clear at a high level. The bits and pieces of context seem to help, that I might leave out if typing and focused more on traditional conciseness / clean writing. With parakeet, I needed to do frequent editing even for shorter bits of speech.
I realize some applications prioritize the latency.
Anytime I’m talking to an Indian on the other end, I have to have them repeat everything 2 or 3 times.
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 in the last mile makes a world of difference.
If anyone has better options, I'm willing to have a look. The best open source solution I found was Handy, and I currently use Wispr Flow
My initial Mac version actually had three additional steps that you could toggle, obviously at the cost of some speed. That is what the website talks about, although nowadays for my own use I've reduced that to just one step and found that it's pretty great. I've got a new version in test to tidy that up, but still lets you define as many steps as you want.
- parakeet usually runs on Bfloat16. NPU doesn't support that
- CPU is not as fast as the NPU for these ops on A-series, and even on modern CPUs, there's a latency delay
- Parakeet latency is fine but "fine" may not be good enough for Apple's UX team.
- CPU increases power consumption over dedicated float blocks
So I would say that Parakeet was a non-option for Apple to ship, although it should be in the benchmarks anyways!
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 that, FluidAudio is ~4.6x and ~4.0x faster.
Superwhisper does a lot more than just provide a whisper/parakeet UI so I’m not sure Apple will destroy them so easily
Even for those sorts of apps, MacParakeet which I've been using is FOSS so no payment needed. In reality these days with AI the ability to spin up a free and/or OSS competitor falls to zero.
A new VAD I found though is FireRedVAD which has better benchmark results than TEN and Silero by far
Also doesn't seem to be tailored to Apple hardware (i.e. no MLX or ANE variant/implementation)
Generally labs don't release MLX or ANE versions and we must rely on finding someone who's converted it
Parakeet is not multilingual so not directly comparable
Where do you see 16GB? MOSS is smaller than Parakeet at 1.82GB
Listen and transcribe felt like the easiest thing to do.
Distavo.com
The source is open for anyone to use, and the builds are in github.
I found quite interesting that claude didn't help too much on how to publish to SetApp until Fable.
What's insane to me is that you have all of these low-quality me-too apps, and literally no one could bother to read the damn Human Interface Guidelines or follow iOS design conventions.
Doing so is literally LESS WORK than trying to make your own custom awful iOS UI.
If you use SwiftUI (the native recommendation by Apple), it severely penalizes you, if you want to paint outside the lines (which is a big reason that I don't use SwiftUI for shipping apps). It's insanely easy to write a native app that is 100% in line with HIG.
(Genuine question - I'm a happy Whisper user but am always looking for improvements).
And if someone were broadly comparing all on-device models (instead of just looking at how this new on-device ones compares to what a specific product uses), Nemotron 3.5's WER are actually a bit higher than what they report for SpeechAnalyzer, for both tests.