Loom de Connor Finnerty
Dual subtitles with romanization for foreign-language video on YouTube, Netflix, iQIYI, and WeTV.
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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.
Evaluat cu 4 de către 4 recenzori
Permisiuni și date
Permisiuni necesare:
- Să îți acceseze datele pentru site-uri din domeniul youtube.com
- Să îți acceseze datele pentru site-uri din domeniul netflix.com
- Să îți acceseze datele pentru site-uri din domeniul nflxvideo.net
- Să îți acceseze datele pentru site-uri din domeniul iq.com
- Să îți acceseze datele pentru site-uri din domeniul iqiyi.com
- Să îți acceseze datele pentru site-uri din domeniul wetv.vip
- Să îți acceseze datele pentru site-uri din domeniul wetvinfo.com
- Să îți acceseze datele pentru site-uri din domeniul video.qq.com
- Să îți acceseze datele pentru site-uri din domeniul myqcloud.com
- Să îți acceseze datele pentru api.loom.nerv-analytic.ai
Colectare de date necesare, conform dezvoltatorului:
- Conținut site-uri web
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- Versiune
- 0.3.0
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- 663,31 KB
- Ultima actualizare
- 3 zile în urmă (27 iun. 2026)
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- Licență MIT
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