79 分 | 作者 mrkn1 14小时前
14 条评论
- piotrrojek 6小时前If someone is interested, this is my supershort zsh/bash scripts that I keep in .zshrc for doing the same thing using plain whisper.cpp, ffmpeg and yt-dlp (`brew install whisper-cpp yt-dlp` for Mac); I output it in vtt format (subtitles) though, but it's easy enough to change it to txt.
plus additional bootstrap script for large-v3-turbo model from my chez-moi dotfiles:yt_to_srt() { local url="$1" local output_base="$2" local language="${3:-en}" yt-dlp -x --audio-format wav --postprocessor-args "-ar 16000" -o "$output_base.wav" "$url" whisper-cli --language "$language" --model "$WHISPER_MODEL" --split-on-word --max-len 65 --output-vtt --output-file "$output_base" --file "$output_base.wav" rm "$output_base.wav" } file_to_srt() { local filepath="$1" local language="${2:-en}" local filename=$(basename "$filepath") local filename_no_ext="${filename%.*}" local output_base="$filename_no_ext" local temp_wav="$output_base.wav" ffmpeg -i "$filepath" -vn -acodec pcm_s16le -ar 16000 -ac 1 "$temp_wav" whisper-cli --language "$language" --model "$WHISPER_MODEL" --split-on-word --max-len 65 --output-vtt --output-file "$output_base" --file "$temp_wav" rm "$temp_wav" }#!/bin/bash # Download whisper.cpp models from Hugging Face (runs once per machine). set -euo pipefail MODELS_DIR="$HOME/whisper-models" BASE_URL="https://huggingface.co/ggerganov/whisper.cpp/resolve/main" MODELS=("ggml-large-v3-turbo.bin" "ggml-tiny.bin") mkdir -p "$MODELS_DIR" for model in "${MODELS[@]}"; do if [ ! -f "$MODELS_DIR/$model" ]; then echo "Downloading $model..." curl -L --progress-bar -o "$MODELS_DIR/$model" "$BASE_URL/$model" else echo "$model already exists, skipping." fi done echo "Whisper models ready at $MODELS_DIR"- ramon156 4小时前yt-dlp can download auto-subtitles and regular subtitles, why not do that and fall back to whisper?
- jorritpr 31分钟前Very cool, I'm also working on a captioning/subtitling project for the lecture recordings for the university I work at.
My biggest challenge is finding a proper language model that is fast enough and accurate enough since I have to caption about 600 hours of video per week and I preferably want to run all of this on a tiny server (2 cores 4 GB memory). This tool could easily do that with the kroko model but I'll have to test if the accuracy is good enough.
Also in my own scripts I'm using ffmpeg to download just the audio of the videos that I want to caption, which saves a lot of bandwith and speeds up the whole process. As far as I can see this tool doesn't do that, that would be a nice functionality to add, plus an option to turn the output into a working .srt file.
- throw98226 4小时前Works extremely well. Command to install on Debian 13:
sudo apt update && sudo apt install -y ffmpeg python3-pip python3-venv && git clone https://github.com/kouhxp/yapsnap.git && cd yapsnap && python3 -m venv ~/yapsnap-venv && source ~/yapsnap-venv/bin/activate && pip install --upgrade pip && pip install .
On a 32GB ThinkPad X13, a 21 minute YouTube video was processed by yapsnap under 2 minutes.
Very well done!
- delis-thumbs-7e 3小时前Am I a bit thick, but first we created this amazing way to transfer any text very cheaply and fast over network, then we (well, I think it was Meta and Google) decided that no, everything must be a video, then we added subtitles and AI-transcriptions to those videos and now we just dowload transcriptions of those videos presumably to feel LLM to make summaries of them in order to… Read. Them.
I think I’m gonna go read a book.
- spudlyo 12小时前So, this project consists of a ~175 line README and a ~500 line Python program that glues yt-dlp and Kroko together. Neat.
I guess if it encourages you to install and figure out how to use ffmpeg, yt-dlp, kroko, numpy, and onnx that's a good thing. Sometimes just knowing a thing is possible is a huge benefit.
- mrkn1 11小时前thank you. You nailed the actual value, that's right. The real win is just knowing you can do this on a laptop CPU, offline, no GPU or cloud bill. There are tiny done-for-you details, like rescaling token timestamps back to real time after the atempo speedup so --timestamps doesn't lie to you, but they are minor.
- mscdex 8小时前Why the choice of Kroko over something like parakeet-tdt-0.6b-v3, which is also faster than realtime on CPU?
- nshm 5小时前Kroko models are more accurate and their size is just a hundred megabytes compared to parakeet (2.5 gigabytes in default fp32)
- mscdex 5小时前Do you have a link to results confirming this? Kroko does not seem to be on the Open ASR Leaderboard. Parakeet has an average WER of 6.32 across several common datasets.
- iririririr 11小时前I see the value as a centralized anti-content-blocker.
This repo is now a good way to centralize hacks around the sure-to-come blockers those platforms will add to prevent download.
Just like uBlockOrigin was a way to centralize all the "just run this greasemonkey script" comments, I can see this getting a huge following for people who really value transcriptions.
- mrkn1 11小时前I appreciate the perspective! higher ceiling than I'd put on it, but if it gets there awesome. PRs welcome!
- niraj-agarwal 11小时前Had Claude test it out on 3 videos. Worked at 5-8x realtime. The beauty of it is that it works on all videos, not just the one with transcripts. Combine it with YouTube search and LLM takeaways from transcripts, and you have super-efficient content consumption. There are SaaS products that charge 1 cent per video for those with transcripts. There is a viable product in here somewhere, methinks.
- mrkn1 10小时前thanks for running it Niraj. I see something similar on my machine, which still surprises me every time lol
- HDBaseT 7小时前Wouldn't it still be more efficient to do GPU transcriptions anyways? is this something we could actually put the effectively useless NPUs to use in modern laptops?
- dharma1 5小时前yes GPU is significantly faster, but cpu only lets you do it anywhere - wasm in the browser, any server etc.
NPUs - definitely a good use case for at least part of it, there are ports of whisper that use coreML/ANE with less power and 3x speed of CPU only
- KingMob 6小时前Possibly, but you may want to use the GPUs for other things, or have under-utilized CPU-only servers lying around.
- 7777777phil 2小时前Tis is very simple and very cool! Just installed it on my Hetzner box where I run a remote controlled local agent so now I can basically chat/email a video link to get a summary and/or ask questions. The only issue was YouTube's PO Token requirement (web/mweb clients refuse to serve formats from datacenter IPs without a valid Proof-of-Origin token.) So I had to find a client that still work without PO Token first. Thanks for sharing!
- canadiantim 8小时前Nice. Can it do speaker diarization?
- dmos62 6小时前Now make it distinguish speakers and we really have something. As far as I know, that's significantly harder though.
- ranger_danger 10小时前How can we transcribe other languages besides English?
- mrkn1 10小时前Just download the model for your preferred language, all hosted on the Kroko-ASR collection here: https://huggingface.co/Banafo/Kroko-ASR/tree/main Right now you have Dutch, French, Portuguese, Spanish, German, Italian, Swedish, Swiss German, Hebrew, and Turkish. Grab the one that matches your audio, point yapsnap at it with --model (or set KROKO_MODEL), and you're set!
- charcircuit 11小时前Most of these platforms already have transcriptions built in.
- mrkn1 11小时前Youtube has transcripts on most videos, not all. The others don't expose them. If you mean the "transcript APIs" for TikTok/IG/X, they are all transcribing audio like yapsnap does. If you have a way to pull native ones, let me know, genuinely curious.
- charcircuit 11小时前YouTube's is transcribing the audio too. The other do expose them as subtitles as the video is playing.
- mrkn1 10小时前Yes fair point, asr cached and exposed. I meant to draw the line more on fetchable or not.
- xnx 11小时前[dead]
- chris_explicare 4小时前[flagged]