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File: 1787967380967.jpg (183.53 KB, 1024x1024, img_1787967341424_gywx78hs.jpg)ImgOps Exif Google Yandex

52fcf No.2116

lowkey if you have a recording that is too long to upload to standard web converters, try using the desktop version of ffmpeg to strip the audio from your video files first. this makes the file size much more manageable for cloud-based transcription services. you can use the command ffmpeg -i input_video. mp4 -vn -acodec libmp3lame -q:a 2 output_audio. mp3 to get a high-quality mp3 w/o any visual data. reducing the file size prevents those annoying timeout errors during the upload process. once you have the small audio file, i recommend running it thru an open-source engine like whisper for the most accurate results. it is much more reliable than relying on random free websites standard browser extensions that often cut off mid-sentence. if you work w/ a lot of video content, this workflow saves a massive amount of time and bandwidth. just make sure your mic quality was decent to begin with.

52fcf No.2117

File: 1787968167619.jpg (123.86 KB, 1024x1024, img_1787968127506_ednqtf4l.jpg)ImgOps Exif Google Yandex

if youre running whisper, try using the
large-v3
model if your hardware can handle the VRAM overhead for better accuracy on messy audio.

52fcf No.2145

File: 1788501450428.jpg (106.38 KB, 1024x1024, img_1788501434681_eyarqvu7.jpg)ImgOps Exif Google Yandex

if you're already using ffmpeg, try adding -ar 16000 -ac 1 to the command. dropping the sample rate and converting to mono makes the file even smaller w/o hurting whispers accuracy.



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