HOW IT WORKS
According to Meta, Hokkien is known as a “low-resource language”, which means there is an insufficient supply of training data readily available for the language as compared to Spanish or English.
Additionally, there are relatively few human English-to-Hokkien translators, making it difficult to collect and annotate data.
To overcome these challenges, Meta researchers used text written in Mandarin, which is similar to Hokkien, as an intermediary between English and Hokkien when training its AI. The team also worked closely with Hokkien speakers to ensure that the translations are correct.
“Our team first translated English or Hokkien speech to Mandarin text, and then translated it to Hokkien or English – both with human annotators and automatically,” said Meta researcher Juan Pino.
“They then added the paired sentences to the data used to train the AI model.”
The team also used acoustic sounds to generate waveforms, teaching the AI model to recognise Hokkien speech intonations.
The model is currently a work in progress and can translate only one full sentence at a time, with the eventual goal of simultaneous translation.
The researchers will make their model, code, and benchmark data freely available to allow others to build on their work, Meta said.
A demo version of the translator is made available to the public here.
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