"Sanjib Chaudhary chanced upon StoryWeaver, a multilingual children’s
storytelling platform, while searching for books he could read to his
7-year-old daughter. Chaudhary’s mother tongue is Kochila Tharu, a language
with about 250,000 speakers in eastern Nepal. (Nepali, Nepal’s official
language, has 16 million speakers.) Languages with a relatively small number of
speakers, like Kochila Tharu, do not have enough digitized material for
linguistic communities to thrive—no Google Translate, no film or television
subtitles, no online newspapers. In industry parlance, these languages are
“underserved” and “underresourced.”
This is where StoryWeaver comes in. Founded by the Indian education nonprofit
Pratham Books, StoryWeaver currently hosts more than 50,000 open-licensed
stories across reading levels in more than 300 languages from around the world.
Users can explore the repository by reading level, language, and theme, and
once they select a story, they can click through illustrated slides (each as if
it were the page of a book) in the selected language (there are also bilingual
options, where two languages are shown side-by-side, as well as download and
read-along audio options). “Smile Please,” a short tale about a fawn’s
ramblings in the forest, is currently the “most read” story—originally written
in Hindi for beginners, it has since been translated into 147 languages and
read 281,000 times.
A majority of the languages represented on the platform are from Africa and
Asia, and many are Indigenous, in danger of losing speakers in a world of
almost complete English hegemony. Chaudhary’s experience as a parent reflects
this tension. “The problem with children is that they prefer to read storybooks
in English rather than in their own language because English is much, much
easier. With Kochila Tharu, the spelling is difficult, the words are difficult,
and you know, they’re exposed to English all the time, in schools, on
television,” Chaudhary said
Artificial intelligence-assisted translation tools like StoryWeaver can bring
more languages into conversation with one another—but the tech is still new,
and it depends on data that only speakers of underserved languages can provide.
This raises concerns about how the labor of the native speakers powering A.I.
tools will be valued and how repositories of linguistic data will be
Via Wayne Radinsky.
*** Xanni ***
Chief Scientist, Xanadu
Partner, Glass Wings
Manager, Serious Cybernetics