But it's a thousand times easier than trying to transcribe things manually! And it even does punctuation and outputs an. It's not quite perfect yet-I still need to touch up probably one word every 10 sentences.It will automatically identify the source language, or you can specify it with -language). You can even translate text files (using -translate), which is a neat trick.
Honestly it blew me away that it picked up words like 'PlinkUSA', 'Sliger', and 'Raspberry Pi'-something other transcription tools would trip on. Experimenting with the different models, base.en was very fast for English, but I found that small or medium were much better at identifying product names, obscure technical terms, etc.I installed it and ran it on one of my video's audio tracks using the commands at the top of this post, and I was pleasantly surprised: And on my earlier blog post about using macOS's built-in Dictation feature for transcription, rasmi commented that a new tool was available, Whisper.
YouTube shows whether a video has manually-curated captions with this handy little 'CC' icon:īut as Veed's free tier only allows up to 10 minutes of audio to be transcribed at a time, it was time to look elsewhere. srt file alongside my video on YouTube, and people are able to use Closed Captions. One thing I do quite regularly for my YouTube channel is extract the audio track, convert it to text using an online tool (I used to use Welder until they were bought out by Veed), and then hand-edit the file to fix references to product names, people, etc. Whisper my_audio_file.mp3 -language English Pip3 install -upgrade -no-deps -force-reinstall git+ Tl dr: # Install whisper and its dependencies. The whisper repository contains instructions for installation and use. Late last year, OpenAI announced Whisper, a new speech-to-text language model that is extremely accurate in translating many spoken languages into text.
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