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Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

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Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#151
post #94
post #64

Earlier quoted context omitted.

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)

Does anyone have any experience with Mandarin STT? What's a good model for this? The use-case I have is subtitling of Mandarin speech.

MOSS-Transcribe-Diarize [0] is by a Chinese team so apparently it's quite good. Try it out here [1].

[0] https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize

[1] https://huggingface.co/spaces/OpenMOSS-Team/MOSS-transcribe-...

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#153

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…

> 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.

No, there are better open weight models: https://artificialanalysis.ai/speech-to-text/non-streaming

Apparently MOSS-Transcribe-Diarize is quite good too as it released only a few days ago.

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#154
post #125

Is this the new dictation engine that I'm not allowed to run on my 1-YEAR-OLD IPHONE 17 because it's not Pro?

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

I hope this is sarcasm.

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#155

Earlier quoted context omitted.

Test it! Does it make network requests? Unplug the internet and see if it still works!

You are being naive. An Apple device makes dozens of network requests every minute or so to Apple. It is neigh on impossible to verify what is being requested or sent. Also unplugging the Internet and verifying that something still works does not mean the app won't phone home behind your back when it can. These things are designed to fail silently.

Download use Little Snitch or

https://alternativeto.net/software/little-snitch/

https://www.g2.com/products/little-snitch/competitors/altern...

There are many alternatives for trying to find out what’s going on. If you don’t want to bother, and most people don’t, well, what else is there to say?

It is generally a good idea to know what software is phoning home, if you can pinpoint it.

If you have any software recommendations, I’d be happy to know.

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#156

Earlier quoted context omitted.

Thanks, was looking at a better diarization model. 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.

I’m not even using it for diarisation just transcription and it’s amazing. It also doesn’t need a VAD A new VAD I found though is FireRedVAD which has better benchmark results than TEN and Silero by far

Is MOSS a streaming model or only for offline? For that VAD how are you integrating it into a model like Whisper etc?

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#157
post #94

Earlier quoted context omitted.

Does anyone have any experience with Mandarin STT? What's a good model for this? The use-case I have is subtitling of Mandarin speech.

MOSS-Transcribe-Diarize [0] is by a Chinese team so apparently it's quite good. Try it out here [1]. [0] https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize [1] https://huggingface.co/spaces/OpenMOSS-Team/MOSS-transcribe-...

Thank you very much.

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#158

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

Turning dialogue audio into text for searchability and accessibility (particularly for deaf users)

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#159
post #129

Earlier quoted context omitted.

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

At the time, there was very little advantage to buying the Pro model. Ironically, it's the first time I've ever bought the base model.

Serves you right

Re: Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

#160

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

The canadian government will provide lots of historical data for curious citizens, many of which are recordings of interviews from decades and decades ago. For a book project this allows me to make a hours of audio searchable through a GUI application I have developed that has a voxtral backend.
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