Loom geliştiren: Connor Finnerty
Dual subtitles with romanization for foreign-language video on YouTube, Netflix, iQIYI, and WeTV.
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Bu uzantı hakkında
Loom: Dual-language subtitles for YouTube, Netflix, iQIYI, and WeTV, with phonetic annotations and romanization.
Loom is a language-learning tool for anyone who watches YouTube, Netflix, iQIYI, or WeTV videos in a language they're studying. It renders TWO subtitle tracks at once - the original (foreign) language on top, your own language on the bottom - so you can follow the dialogue without switching back and forth.
For non-Latin scripts, Loom adds a romanization line above the foreign text (eg "konnichi wa" above "こんにちは") so you can read along even before you learn the characters. For CJK languages it additionally adds per-character readings: furigana for Japanese, Pinyin or Zhuyin for Chinese, Jyutping for Cantonese, Revised Romanization for Korean. For Traditional Chinese, Loom can also show the Simplified form of each character above it.
iQIYI and WeTV are especially good for Chinese learners - most of their dramas offer a selectable Chinese subtitle track, which Loom reads and annotates with Pinyin.
Every visual aspect is customizable: per-layer colors, fonts, sizes, outlines, glow, and opacity. 28 thematic color presets ship out of the box. Settings persist per device. Loom works on any video that has a selectable text subtitle track in your target language (on YouTube, that means human-made or auto-generated captions).
Loom is a research project from nerv-analytic.ai. It's free, has no ads, and collects no personal data - the only thing it ever sends out of your browser is subtitle text, used solely to generate the romanization. See the privacy policy at loom.nerv-analytic.ai/privacy for details.
Loom is a language-learning tool for anyone who watches YouTube, Netflix, iQIYI, or WeTV videos in a language they're studying. It renders TWO subtitle tracks at once - the original (foreign) language on top, your own language on the bottom - so you can follow the dialogue without switching back and forth.
For non-Latin scripts, Loom adds a romanization line above the foreign text (eg "konnichi wa" above "こんにちは") so you can read along even before you learn the characters. For CJK languages it additionally adds per-character readings: furigana for Japanese, Pinyin or Zhuyin for Chinese, Jyutping for Cantonese, Revised Romanization for Korean. For Traditional Chinese, Loom can also show the Simplified form of each character above it.
iQIYI and WeTV are especially good for Chinese learners - most of their dramas offer a selectable Chinese subtitle track, which Loom reads and annotates with Pinyin.
Every visual aspect is customizable: per-layer colors, fonts, sizes, outlines, glow, and opacity. 28 thematic color presets ship out of the box. Settings persist per device. Loom works on any video that has a selectable text subtitle track in your target language (on YouTube, that means human-made or auto-generated captions).
Loom is a research project from nerv-analytic.ai. It's free, has no ads, and collects no personal data - the only thing it ever sends out of your browser is subtitle text, used solely to generate the romanization. See the privacy policy at loom.nerv-analytic.ai/privacy for details.
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İzinler ve veriler
Gerekli izinler:
- youtube.com alan adındaki sitelere ait verilerinize erişme
- netflix.com alan adındaki sitelere ait verilerinize erişme
- nflxvideo.net alan adındaki sitelere ait verilerinize erişme
- iq.com alan adındaki sitelere ait verilerinize erişme
- iqiyi.com alan adındaki sitelere ait verilerinize erişme
- wetv.vip alan adındaki sitelere ait verilerinize erişme
- wetvinfo.com alan adındaki sitelere ait verilerinize erişme
- video.qq.com alan adındaki sitelere ait verilerinize erişme
- myqcloud.com alan adındaki sitelere ait verilerinize erişme
- api.loom.nerv-analytic.ai verilerinize erişme
Toplanması gereken veriler (geliştiriciye göre):
- Web sitesi içeriği
Daha fazla bilgi
- Eklenti bağlantıları
- Sürüm
- 0.3.0
- Boyut
- 663,31 KB
- Son güncelleme
- 3 gün önce (27 Haz 2026)
- İlgili kategoriler
- Lisans
- MIT Lisansı
- Gizlilik ilkeleri
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