Hacker News

Whisper v3 is still the best (by far) when it comes to poor quality input (say background audio from a security camera), though remains more susceptible to hallucination so it's a bit of a tradeoff.

Also, this test is English-only, while a strong point of other models is to understand different languages without first having to say which one (so you don't need 3 different keyboard shortcuts if you wanna dictate in 3 languages day-to-day)

> there are better models that are state of the art now like Nemotron and Parakeet both by Nvidia

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.

Apple's own Voice Memos app already does automatic transcription since macOS 15 / iOS 18.

Of these only Parakeet is <1B, it looks better than Apple's model, however it's not builtin. I wonder how it compares on latency and efficiency.

I hope they replace their awful voice to text on their keyboard. I can't stand that terrible bit of software.

Yeah, apple will be optimizing a model to work on ANE and then turn it into a native app. My only hope is that it has a reasonable api so that I can use that as a generic input source across iOS / macOS that’s equivalent to the ubiquity of the keyboard.

> 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 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

I don’t know how Apple divides computation between the GPU and the Neural Engine, but one major benefit, especially for real-time transcription on laptops, is the improved power and thermal efficiency. I noticed better accuracy after switching my app to SpeechAnalyzer, and I suspect part of that improvement for me came from the microphone no longer having to compete with jet-engine fan noise.

For multilingual and noisy audio the best right now is MOSS-Transcribe-Diarize which was released just a few days ago

Superwhisper does a lot more than just provide a whisper/parakeet UI so I’m not sure Apple will destroy them so easily

I’m not sure I agree. There may be better models, but the comparison is still useful so long as whisper is so widely used.

I am curious, what are the use cases people are using voice transcription for?

I use handy.computer and it is pretty much everything I want from a transcribing app.

Hey. Yes. I did vive code one as an exercise yo learn how to publish to apple store.

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.

> 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 seems to be vibe coding these days.

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.

How many of the Whisper competitors will work at a reasonable speed using only CPU (on Linux, not Apple)?

(Genuine question - I'm a happy Whisper user but am always looking for improvements).

This particular product used Whisper, so that was obviously the right model to compare it against. Further this is explicitly on device, and Nemotron 3.5, as one example, is 2.5GB for the model.

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.

Came here to post this. I use handy on my own machine and it's perfect with parakeet. If I switch to whisper it makes lots of mistakes

Been using it for a podcast app I have been developing for half a year lol (I hope I publish it by version 27) and I can confirm it’s real fast.

Splitting the audio in multiple segments and firing it up without hitting the maximum limit of concurrent decoding streams makes it blazing fast. Fair enough you loose the cut, but it’s good enough for just podcast. In one minute it chews through one hour of audio. This on an iPhone 17 Pro.

If it was faster but worse, maybe compare it to a smaller whisper model?

I typically disable autocorrect on Apple products because of this, cautiously optimistic about their improved speech models, but definitely worried that it's going to 'correct' technical jargon to more common words.

There are many [0], you can search and filter by streaming and open weight only as well.

Looks like Voxtral and Nvidia's Nemotron are best.

[0] https://artificialanalysis.ai/speech-to-text/non-streaming

There's tons, Parakeet was the last I remember seeing which seemed to gain traction (independent lightweight implementations etc).

Why did you buy the cheap one, that's your own fault

For just desktop, I use Handy (open source): https://handy.computer/

And yea, Nvidia's Parakeet v3 is good enough for my own just local transcription most of the time.

When I need local transcription to be more reliable and I don't have the energy to proof read a long ramble, I still often just pop open chatGPT, dictate, cut, paste.

But we're pretty much already to the point where local transcription models can replace cloud ones for personal use. They're still a bit rough around the edges in terms of polish and latency, but plenty of people are fine with that to avoid yet another app subscription and not having to worry about wondering what's potentially happening with their data.

Try MOSS-Transcribe-Diarize from a few days ago. I’m getting better results than those whisper models. And it’s very fast and small. Better suited to noisy audio too.

Same with the keyboard. Apple is completely incapable of taking context into account for the input mechanisms of the operating system.

If I start typing and the existing text is in Spanish, then a sensible default is to select the Spanish keyboard I have installed and let me adjust otherwise.

App developers should also be allowed to supply mini-dictionaries within a context to allow autocorrect to work correctly in that context, so for example in this thread [SpeechAnalyzer, API, Whisper, Parakeet, Nemotron] should be supplied so that these terms are autocorrected.

I don’t like it written that way either, and it always seems like the type of number you put on a slide for a head of sales or something. It rankles because:

- it implies that error could be increased n-times, but a 15x _increase_ in 9% error would be an error rate of 135%, which is nonsensical.

- a reduction from 90% error to 20% error is clearly a bigger improvement in rightness to a reduction from 9% to 2%. One is “almost all wrong to almost all right”, the other is “more right”, but they are both a 4.5x reduction in error which means that the 4.5 quantity doesn’t have a constant meaning.

The answer is something like log odds ratios, but that introduces the additional need for a reader to know what that is, and that would be unusual.

well, it's nice, but the multi-lingual diff is rather limited (only European languages).

No, this is the current dictation functionality on iOS 26.

I'd be interested too. Last time I looked the state of the art was pretty bad.

Probably not worth the effort (or legal trouble), unless you can show it's better than other recent open models like Cohere Transcribe.

Is that copyright infringement?

Aside from the legality of it, I think you are underestimating how complex it can be to do that. It is possible in theory but not something that will be a fun side quest like you are making it seem.

Yeah, ChatGPT voice is great experience vs. Siri on that phone. In case you haven't done something like this already:

  1. In Shortcuts app, make shortcut named "AI Voice Mode" (or whatever you want, YMMV)
  2. Set it to run the ChatGPT action "Voice Mode" (requires at least the minimum paid tier, I think)
  3. To trigger, say "Hey Siri, AI Voice Mode" (or whatever you called the shortcut)

I’m on iPhone 17 Pro Max, 27 beta 3.

New Siri is impressive in that it answers satisfactorily now 80% of the time vs 10% with old Siri.

But it’s slow as shit. GPT, Claude, and Gemini can answer me in 5-10 seconds. Google AI Mode can answer in 2 seconds.

New Siri usually takes 25 seconds to respond to me. This morning it timed out (with strong network connection) when asked a simple multiplication question.

> Im hoping Apple gets the new Siri working better on older phones.

Apple would never do that, if anything they did not offer their Siri with the most advanced AI on iPhone 16 Pro Max, which is one year-old only.

At this point, I would not recommend ignoring Parakeet TDT 0.6b v2/v3 (english-only versus multilingual). Those models have been out for a year, give or take, and they are both accurate and fast. I would choose Parakeet over Whisper in almost all situations these days. Parakeet works great even on my several year old iPhone 15 Pro Max, so if an app is going to ship a dedicated model, I strongly recommend investigating Parakeet.

On the more cutting edge front, Granite Speech 4.1 has proven to be a reliable workhorse for me, but it is larger than Parakeet. Cohere Transcribe is interesting, but how strong it is seems to vary more from task to task.

Parakeet Unified 0.6B came out a few months ago, combining both online streaming and offline transcription into one model, and that is one that I need to test more, but it seems promising.

As others have mentioned macOS 27/iOS 27 is supposed to have a new model, particularly on devices with 12GB of RAM or more. I have not actually seen the option to enable that new model yet, though, despite being on the beta on a device that meets the requirements. Maybe a benchmark would reveal that it is already active?

Why do you not use Whisper large models when on macOS? They're still fast even when streaming and yield a much lower WER.

Also, just out of curiosity, seems like everyone and their mother is making Whisper wrappers, how is your app different?

Why use relatively ancient models like whisper and not e. g. parakeet?

Please run your benchmark on this new and very impressive model https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize in my testing it outperforms all mentioned especially on noisy audio

MOSS-Transcribe-Diarize

Which OpenAI model/API do you mean?

In which world 98% accuracy is not usable?

agreed. plus all the languages supported!

It's a local model so it's essentially open weight such that you could feasibly export it somehow since it's already on the laptop somewhere. Apfel is a wrapper app like ChatGPT but using Apple Foundation Models, I assume something similar will happen with this transcription model.

https://apfel.franzai.com/

It's not open weight, but the point is to be an on device (and thus local, privacy preserving) option. The article mentions that as the caveat

> What this means if you just want good transcription

> If you are on a current iPhone or Mac, the best on-device transcription engine for English is already in the operating system, and the private option is no longer the compromise option

It is local

The appeal is that users only have to download it once across all apps that use it. Instead of convincing a user to give a couple gigs for just your one app