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Automated Japanese vocabulary mining from anime subtitles with Anki integration

Project description

Anki Miner

PyPI version License: GPL v3 Python 3.10+

Batch-mines Japanese vocabulary from anime and YouTube into Anki cards. Given a season folder or a YouTube URL, it produces cards containing screenshots, sentence audio, furigana, pitch accent, and frequency data.

Suited to batch processing after viewing, rather than real-time lookup during playback (the asbplayer and Yomitan workflow).

Showcase

Anki Miner Showcase

Example cards

Cowboy Bebop Frieren Steins;Gate

Generated from video and subtitle files. Each card contains a screenshot, sentence audio, furigana, and definition.

How It Works

  1. Parse subtitles: tokenize Japanese text with MeCab morphological analysis.
  2. Filter words: keep content words (nouns, verbs, adjectives, adverbs); drop words already in your Anki collection or on your blacklist.
  3. Extract media: capture screenshots and audio clips from the video at each subtitle's timestamp via ffmpeg.
  4. Fetch definitions: look up English definitions from JMdict (offline) or the Jisho API.
  5. Create cards: batch upload to Anki via AnkiConnect.

Features

  • Lapis-compatible cards with furigana, pitch accent, and word frequency fields.
  • YouTube support: paste a URL, mine the video.
  • Queue a folder of episode/subtitle pairs for sequential processing.
  • Offline JMdict dictionary with Jisho API fallback.
  • Preview and curate the word list before any cards are created.
  • Parallel ffmpeg extraction for screenshots and sentence audio.
  • Analytics dashboard with history, undo, and series difficulty rankings.
  • Four themes (Light, Dark, Sakura, Tokyo Night) plus custom JSON themes.

Installation

Requirements

  • ffmpeg on PATH.
  • Anki with the AnkiConnect add-on. In Anki: Tools → Add-ons → Get Add-ons, paste code 2055492159, restart.

Download

Grab the installer for your platform from the latest release:

Platform Installer Portable
Windows AnkiMiner-*-Setup.exe AnkiMiner-Windows-x86_64.zip
Linux (Debian/Ubuntu) anki-miner_*_amd64.deb AnkiMiner-*-Linux-x86_64.AppImage
Linux (other) AnkiMiner-Linux-x86_64.tar.gz
macOS (Apple Silicon) AnkiMiner-macOS-arm64.tar.gz

No Python required. Installers and portable archives bundle all dependencies.

Install from PyPI (Python 3.10+)
pipx install anki-miner   # or: pip install anki-miner
Install from source
git clone https://github.com/0xzerolight/anki_miner.git
cd anki_miner
pip install .

Quick Start

After installing, launch Anki Miner from your Start Menu, Applications folder, or app menu. If you installed from PyPI or source, run anki_miner_gui from a terminal. A desktop shortcut is created on first launch; re-run it from Tools → Create Desktop Shortcut... inside the app.

Anki must be running with AnkiConnect installed before mining starts.

Tabs:

  • Single Episode: mine one video/subtitle pair with file selectors and progress tracking.
  • Batch Processing: queue multiple series for sequential processing.
  • YouTube: paste a URL, fetch metadata, then mine.
  • Analytics: history, series difficulty, milestones.
  • Settings: Anki connection, media extraction, dictionary, word filtering. Saved to ~/.anki_miner/gui_config.json.

Recommended Setup

Lapis Note Type

Anki Miner uses the Lapis note type fields by default.

  1. Download the latest .apkg from Lapis releases.
  2. In Anki: File → Import and select the .apkg.

Default field mapping:

Anki Miner Field Note Field Content
word Expression Dictionary form of the word
sentence Sentence Original subtitle line
definition MainDefinition English definitions
picture Picture Screenshot from the video
audio SentenceAudio Audio clip of the sentence
expression_furigana ExpressionFurigana Word with furigana reading
sentence_furigana SentenceFurigana Sentence with furigana reading
pitch_position (unmapped) Pitch accent position number
pitch_category (unmapped) Pitch accent category
frequency (unmapped) Word frequency rank

Fields marked (unmapped) have no default Lapis mapping. Map them in Settings if your note type has equivalents. Any note type with the required fields works.

JMdict Offline Dictionary

For fast offline lookups:

mkdir -p ~/.anki_miner
wget -O ~/.anki_miner/JMdict_e.gz http://ftp.edrdg.org/pub/Nihongo/JMdict_e.gz
gunzip ~/.anki_miner/JMdict_e.gz

Without JMdict, lookups fall back to the Jisho API (slower, online, rate-limited).

YouTube Mining

Paste a URL, click Fetch Info to probe metadata (title, duration, subtitle availability), then click Mine. The fetch downloads the video and its Japanese subtitle track into a per-run temporary directory, then passes both files to the same pipeline used for file-based mining.

Auto-captions are accepted only when native Japanese. Tracks that YouTube generates by machine-translating from English are rejected, since mining them yields unusable results. Native auto-captions remain lower quality than manual subtitles because they lack sentence boundaries.

Gotchas:

  • Bot-detection prompts: if YouTube asks "Sign in to confirm you're not a bot", open Settings → Cookies → Browser and pick Firefox or Chrome. yt-dlp pulls cookies from that browser's profile on every fetch.
  • Age-restricted videos: same fix.
  • Max duration: defaults to 120 minutes. The probe aborts before downloading if the video is longer. Adjust in Settings.

Troubleshooting

Issue Solution
"Cannot connect to Anki" Start Anki and ensure AnkiConnect is installed.
"Deck not found" Create the deck in Anki or update the deck name in Settings.
"Note type not found" Import Lapis (see above) or configure your own in Settings.
"ffmpeg not found" Install ffmpeg and add it to PATH.
"JMdict file not found" Download to ~/.anki_miner/ (see above) or disable offline dictionary.
Audio is wrong language The tool tries Japanese audio tracks first, then falls back to the default.
Subtitles out of sync Use the subtitle offset control in the GUI.

Issues and Contributing

Bug reports and feature ideas go in Issues. See CONTRIBUTING.md for development setup.

License

GNU General Public License v3.0. See LICENSE.

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