Japanese subtitle generation

When a video has no Japanese subtitles, SubMiner can transcribe its audio into a Japanese SRT with whisper.cpp. Everything runs on your computer. You only need internet access to download a model.

Setup

1. Install whisper.cpp's whisper-cli and FFmpeg (including ffprobe). SubMiner downloads models but not these programs.
2. Make sure they are on your PATH, or set their paths under Settings > Integrations > Japanese Subtitle Generation (whisperPath, ffmpegPath, ffprobePath).
3. Pick a model. Either choose one in the generation modal and click Download model, or set subtitleGeneration.modelPath to a multilingual whisper.cpp GGML .bin file you already have. English-only models and Python Whisper checkpoints do not work.

Downloaded models go to models/whisper/ next to your SubMiner config file. A configured modelPath always wins over the modal's choice.

YouTube videos can use the same setup automatically in place of YouTube's captions. See Generate subtitles with Whisper.

The modal's Local tools section lists anything missing. After you install a tool or change a path, click Check again.

Generating from the overlay

1. Open a local video in mpv and select its Japanese audio track, or play a Jellyfin or YouTube video.
2. Press Ctrl+Shift+G. If the subtitle sidebar is empty, its Generate Japanese subtitles button opens the same modal.
3. Pick a model and download it if needed.
4. Optionally check Focus on spoken dialogue (see below).
5. Click Generate subtitles.

The modal shows progress. Cancel stops the job. Closing the modal lets the job keep running, and reopening it shows the progress.

SubMiner saves <video>.ja.generated.srt next to the video and adds a number if that name is taken. If the same file is still playing, it loads the subtitles and resets the subtitle delay.

For a Jellyfin video, SubMiner reads the original file from your server and saves the subtitles to ~/.cache/subminer/generated-subs/, since a stream has no folder of its own. Each Jellyfin generation replaces the previous file there. Playback keeps going while it works. If Jellyfin is transcoding, SubMiner transcribes the audio track that playback started with.

For a YouTube video, SubMiner downloads its audio first and pauses the video until the subtitles load. The subtitles are temporary, and the audio is deleted when generation ends or you switch videos. See YouTube integration.

Change the shortcut with shortcuts.openSubtitleGeneration.

Generating from the launcher

subminer generate-subs                                  # current mpv file and audio track
subminer generate-subs episode.mkv --download-model
subminer generate-subs episode.mkv --model-path /path/to/ggml-small.bin

Flag	What it does
--model <name>	Use this managed model, such as small or large-v3-turbo
--download-model	Download the managed model if it is missing
--model-path <path>	Use an existing model file
--audio-stream <index>	Pick an audio stream by its absolute FFmpeg index
--output <path>	Write to this SRT path. Existing files are never overwritten.

With a file argument, SubMiner uses the audio stream tagged Japanese, or the first stream. Ctrl+C cancels. The launcher only works with local files. Use the overlay for Jellyfin and YouTube.

Choosing a model

The modal recommends large-v3-turbo if it finds an NVIDIA GPU (nvidia-smi) and your whisper-cli can use CUDA. Otherwise it recommends small. AMD, Vulkan, and Apple GPUs do not trigger the turbo recommendation. The recommendation does not change your settings.

Model	Tradeoff
tiny, base	Fast and small, more recognition errors
small	Balanced quality and CPU time
medium, large-v1/v2/v3	More accurate, needs more memory and time
large-v3-turbo	Faster than large-v3 with a small accuracy loss

Quantized variants (-q5_0, -q5_1, -q8_0) use less disk and memory, with some accuracy loss. Your pick in the modal lasts for the session. Set subtitleGeneration.managedModel to change the default.

Prioritizing spoken dialogue

Focus on spoken dialogue uses a speech detection (VAD) model to drop silent stretches before transcription. Long passages are split near detected speech, which reduces subtitles that appear before the line is spoken.

It needs two extra pieces:

• The Silero VAD model. Click Download speech detection model in the modal, or set vadModelPath to your own Silero GGML model.
• whisper.cpp's speech segment detector, found as whisper-vad-speech-segments or vad-speech-segments on PATH. Set vadPath for any other location.

The checkbox lasts for the session. Setting vadModelPath turns it on by default.

Dialogue mode keeps music and background sound that might contain speech, so songs can still produce subtitles. It can also take longer than a plain run, because each passage is transcribed separately.

Using loaded subtitles as timing references

If the video playing in mpv already has a dialogue subtitle track loaded, SubMiner uses its cue times to decide where to split long audio. This works with or without dialogue mode. Whisper still writes the Japanese text and final timestamps. The launcher uses a reference only when its input is the file open in mpv.

SubMiner prefers English tracks and tracks labeled full or dialogue. It skips forced, image-based, generated, and signs or songs tracks, based on their titles and file names. An unlabeled signs-only file can slip through.

The reference must be timed correctly for the video. SubMiner does not fix a mistimed reference.

Limitations

• Only local files and their internal audio tracks are supported. Not URLs, and not a separate audio file loaded in mpv. Pass a separate local audio file to the launcher instead.
• Whisper can miss, repeat, or invent lines, and its timing is approximate, especially over music or overlapping speech. Check the text and audio when you mine.
• SubMiner does not translate subtitles.