# Voice recognition

DevFeed: [Voice recognition](<https://devfeed.tech/articles/voice-recognition-36609.md>)

Original publisher: [Read original article](<http://www.imperialviolet.org/2023/07/29/voice-recognition.html>)

Author: Adam Langley

Published: 2023-07-29T00:00:00Z

Content type: opinion

Language: en

Sources: [ImperialViolet](<https://devfeed.tech/sources/imperialviolet.md>)

Topics: [Whisper](<https://devfeed.tech/topics/whisper.md>), [iOS](<https://devfeed.tech/topics/ios.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [caveat](<https://devfeed.tech/tags/caveat.md>), [ios](<https://devfeed.tech/tags/ios.md>), [llms](<https://devfeed.tech/tags/llms.md>), [performance](<https://devfeed.tech/tags/performance.md>), [script](<https://devfeed.tech/tags/script.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [voice](<https://devfeed.tech/tags/voice.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

## AI overview

The author compares iOS 17 voice recognition with earlier results and finds that, although performance improved over iOS 16, it still produces too many errors with technical terms. The article then reports that Whisper solved the practical voice-recognition problem, while noting that it can append fabricated sentences that are removable.

## Source excerpt

Update: Evan let me know that Whisper solved the voice recognition problem. He has a wrapper that records from a microphone and prints the transcription here. Whisper is very impressive and the only caveat is that it sometimes inserts whole fabricated sentences at the end. The words always sort of make sense in context, but there were no sounds that could possibly have caused it. It's always at the very end in my experience, and it's no problem to remove it so, with that noted, you should ignore everything below because Whisper is a better answer. Last week's blog post was rather long, and had a greater than normal number of typos. (Thanks to people who pointed them out. I think I've fixed all the ones that were reported.) This was because I saw in reviews that iOS 17's voice recognition was supposed to be much improved, and I figured that I'd give it a try. I've always found iOS's recognition to be superior to Google Docs and I have an old iPad Pro that's good for betas. iOS's performance remains good and, yes, I think it's better than iOS 16. But it's still hardly at the level of "magic", especially when using technical terms. Here's a paragraph taken directly from the raw output of last week's post (I've highlighted errors with italics): It is integrated into the W3C credential management specification and so it is called via navigator . credentials . create and navigator .credentials. get. This document is about understanding the deeper structures that underpin web orphan rather than being a guy as to its details. So we will leave a great many details to the numerous guides to Web Oran that already exist on the web and instead focus on how structures from UF were carried over into Web orphan and updated. While it's nice that many of the words are there, with that density of errors doing all the corrections means that it's not clearly better than typing things out. However, the world is all aflutter about LLMs these days. Can they help? I wrote a script to chunk