Saiki

Saiki (採記) is a small toolkit for Anki-based language learning workflows: listening playlists, word mining, YouTube transcript mining, TTS sentence imports, and known/new word comparison.

The name is a coined Japanese compound from 採 as in gathering/collecting and 記 as in remembering or recording. Pronunciation: saiki, roughly "sigh-key".

./saiki.py --help

Requirements

• Python 3.12 recommended
• Anki with AnkiConnect
• ffmpeg
• Python dependencies from requirements.txt
• Optional extra TTS backend tools: piper, espeak-ng, and kokoro-onnx.
• spaCy models for word mining:

python -m spacy download es_core_news_sm
python -m spacy download ja_core_news_lg

Setup example:

python3.12 -m venv ~/.venv/saiki
source ~/.venv/saiki/bin/activate
python3 -m pip install -U pip
pip install -r requirements.txt
sudo dnf install ffmpeg

Optional TTS Backends

The default edge-tts backend is installed by requirements.txt. Install only the optional pieces you plan to test:

# Python-backed optional engines: piper, kokoro.
pip install -r requirements-tts.txt

# System package for espeak-ng.
sudo dnf install espeak-ng

Other package-manager names:

sudo apt-get install espeak-ng
sudo pacman -S espeak-ng

Backend notes:

• edge-tts: installed by pip install edge-tts; no API key, but it uses Microsoft Edge's online TTS service.
• gtts: installed by requirements.txt; no API key, but it uses Google's online TTS service through gtts-cli.
• piper: installed by pip install piper-tts; you still need a compatible .onnx voice model, usually with its matching .onnx.json config file.
• espeak-ng: installed through your OS package manager, not pip.
• kokoro: installed by pip install kokoro-onnx soundfile; you still need kokoro-v1.0.onnx and voices-v1.0.bin, plus any language-specific G2P setup required by your Kokoro release.

Example model downloads for the README smoke tests:

mkdir -p ~/.local/share/saiki/models

# Piper Spanish voice model plus matching config.
wget -O ~/.local/share/saiki/models/es_ES-davefx-medium.onnx \
  https://huggingface.co/rhasspy/piper-voices/resolve/main/es/es_ES/davefx/medium/es_ES-davefx-medium.onnx
wget -O ~/.local/share/saiki/models/es_ES-davefx-medium.onnx.json \
  https://huggingface.co/rhasspy/piper-voices/resolve/main/es/es_ES/davefx/medium/es_ES-davefx-medium.onnx.json

# Kokoro ONNX model plus voices bundle.
wget -O ~/.local/share/saiki/models/kokoro-v1.0.onnx \
  https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/kokoro-v1.0.onnx
wget -O ~/.local/share/saiki/models/voices-v1.0.bin \
  https://github.com/thewh1teagle/kokoro-onnx/releases/download/model-files-v1.0/voices-v1.0.bin

Saiki's default tts_model_dir is ~/.local/share/saiki/models. Relative model paths such as es_ES-davefx-medium.onnx are resolved under that directory. You can override it in YAML with tts_model_dir or for one command with --tts-model-dir.

Configuration

Defaults are built in, but you can override them with YAML:

~/.config/saiki/config.yaml

Or pass a config explicitly:

./saiki.py --config ./config.yaml words jp

Example:

anki_connect_url: http://localhost:8765
media_dir: ~/.var/app/net.ankiweb.Anki/data/Anki2/User 1/collection.media
audio_output_root: ~/Languages/Anki/anki-audio
word_output_root: ~/Languages/Anki/anki-words
sentence_dir: ~/Languages/Anki
tts_model_dir: ~/.local/share/saiki/models
note_model: Basic
fields:
  front: Front
  back: Back
languages:
  jp:
    name: japanese
    transcript_code: ja
    tts_backend: edge-tts
    tts_voice: ja-JP-NanamiNeural
    tts_tempo: 1.15
    decks: ["日本語"]
    field: Back
    word_model: ja_core_news_lg
    sentence_file: sentences_jp.txt
  es:
    name: spanish
    transcript_code: es
    tts_backend: edge-tts
    tts_voice: es-ES-ElviraNeural
    tts_tempo: 1
    decks: ["Español"]
    field: Back
    word_model: es_core_news_sm
    sentence_file: sentences_es.txt

A copyable template is also available at examples/config.yaml.

Supported language codes by default:

• jp
• es

CLI

Audio

Extract audio referenced by [sound:...] tags from configured decks and create an .m3u playlist.

./saiki.py audio jp
./saiki.py audio es --concat
./saiki.py audio jp --media-dir ~/.local/share/Anki2/User\ 1/collection.media --copy-only-new

Outputs go to ~/Languages/Anki/anki-audio/<language>/ by default.

Words

Extract frequent words from Anki notes using AnkiConnect and spaCy.

./saiki.py words jp
./saiki.py words es --deck "Español"
./saiki.py words es --query 'deck:"Español" tag:youtube'
./saiki.py words jp --min-freq 3 --out words_jp.txt
./saiki.py words jp --full-field

Output format:

word frequency

Examples:

comer 12
hablar 9
行く (行き) 8
見る (見た) 6

YouTube

Mine vocabulary or sentence rows from YouTube subtitles.

./saiki.py youtube es VIDEO_ID
./saiki.py youtube es VIDEO_ID --top 50
./saiki.py youtube jp VIDEO_ID --mode sentences
./saiki.py youtube es VIDEO_ID --raw --no-stopwords

Export Anki-ready sentence rows:

./saiki.py youtube es VIDEO_ID --mode sentences --out youtube.tsv

Export only rows that appear to contain unknown vocabulary:

./saiki.py youtube es VIDEO_ID \
  --mode sentences \
  --out youtube_new.tsv \
  --known-words ~/Languages/Anki/anki-words/spanish/words_es.txt \
  --only-new

Sentence exports contain:

sentence    timestamp    video_url    vocab_guess

Import

Generate TTS audio and add sentence cards to Anki.

./saiki.py import es
./saiki.py import jp ~/Languages/Anki/sentences_jp.txt
./saiki.py import es youtube.tsv --tags youtube,manual
./saiki.py import es --tts-voice es-MX-DaliaNeural

The importer accepts plain text sentence files and TSV/CSV files with a sentence column. text-to-speech is always added as a tag. If --tags is not provided, AI-generated is added.

TTS is configured per language with tts_backend. Supported backends are:

• edge-tts: default backend using Microsoft Edge neural voices; configure tts_voice.
• gtts: free backend using gtts-cli; configure tts_code and tts_tld.
• piper: local/offline neural TTS; configure tts_model with a model path. The stock Piper catalog includes Spanish voices, but not Japanese.
• espeak-ng: local/offline lightweight TTS; configure tts_voice. Spanish is supported; Japanese is documented as kana-only and is not recommended for normal Japanese sentence cards.
• kokoro: local/offline neural TTS; configure tts_model, tts_voices, tts_voice, and tts_code; some Japanese setups also need tts_vocab_config. Kokoro lists Japanese and Spanish voices, but upstream notes that non-English quality can be thin.

You can override backend settings for one import:

./saiki.py import jp sentences_jp.txt \
  --tts-backend edge-tts \
  --tts-voice ja-JP-KeitaNeural

Voice-listing helpers:

./saiki.py tts-voices jp
./saiki.py tts-voices es --backend edge-tts

Test a TTS backend without creating Anki cards:

./saiki.py tts-test es --out /tmp/saiki_edge_default_es.mp3
./saiki.py tts-test jp --tts-backend edge-tts --tts-voice ja-JP-NanamiNeural --out /tmp/saiki_edge_jp.mp3
./saiki.py tts-test es --tts-backend edge-tts --tts-voice es-ES-ElviraNeural --out /tmp/saiki_edge_es.mp3
./saiki.py tts-test es --tts-backend gtts --tts-code es --tts-tld es --out /tmp/saiki_gtts_es.mp3
./saiki.py tts-test es --tts-backend piper --tts-model es_ES-davefx-medium.onnx --tts-config es_ES-davefx-medium.onnx.json --out /tmp/saiki_piper_es.mp3
./saiki.py tts-test es --tts-backend espeak-ng --tts-voice es --out /tmp/saiki_espeak_es.mp3
./saiki.py tts-test es --tts-backend kokoro --tts-model kokoro-v1.0.onnx --tts-voices voices-v1.0.bin --tts-voice ef_dora --out /tmp/saiki_kokoro_es.mp3

For kokoro, put tts_model, tts_voices, and any needed tts_vocab_config in your config file rather than typing every path each time.

Known/New Words

Compare any generated word list against an existing known list:

./saiki.py compare-words transcript_words.txt ~/Languages/Anki/anki-words/spanish/words_es.txt

This prints entries from the first file whose word key does not appear in the second file.

Card Assumptions

The default configuration assumes Basic notes with audio on Front and the target-language sentence on Back. Word mining reads only the first visible line by default; use --full-field to process the whole field.

To Do

• Add support for different Anki note/card types, including configurable field mappings per language and per import workflow.
• Support multiple import profiles, such as sentence cards, vocab cards, audio cards, and cloze cards.
• Let YouTube exports map directly into configurable note fields, not just a fixed sentence column.
• Add richer transcript filtering, such as minimum/maximum sentence length, duplicate removal, and punctuation cleanup.
• Add optional audio slicing from videos when timestamp data is available.
• Improve known/new word matching with better lemmatization for transcript vocabulary.
• Add more language profiles beyond Japanese and Spanish.
• Add a dry-run mode for imports that previews notes before sending anything to AnkiConnect.
• Build a GUI for common workflows like transcript review, sentence selection, import previews, and configuration editing.
• Add integration tests with mocked AnkiConnect responses.
• Add shell completion or a small installed command once packaging becomes useful.

Tests

Pure logic tests use the standard library test runner:

python -m unittest discover -s tests

License

This project is licensed under the MIT License. See LICENSE.