Meta has launched a new language technology partner program aimed at improving AI translation for underserved languages by sourcing speech recordings, text, and translations from collaborators. Notable representatives, such as the government of Nunavut, have committed to providing data in Inuit languages. Participants will work with Meta's research teams and have access to open-source models, as part of a broader initiative that includes cooperation with UNESCO and the development of various translation systems.

1. Meta Launches ‘Language
Technology Partner Program’
to Source AI Translation Data
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On February 7, 2025, Meta
announced its new Language
Technology Partner Program, which
looks for collaborators to help
improve and expand its op
The Fundamental AI Research (FAIR)
team’s latest initiative at Meta (side
note: FAIR previously stood for
Facebook AI Research) prioritizes
what it calls “underserved
languages” and aligns with the
International Decade of Indigenous
Languages program at the United
Nations Educational, Scientific and
Cultural Organization (UNESCO).

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Specifically, the company is looking for
partners that can contribute speech
recordings with transcriptions, written
text, and translated sentences for low-
resource languages. The Government of
Nunavut, Canada, for example, has
already joined the program, pledging to
share data in the Inuit languages
Inuktitut and Inuinnaqtun.
Those interested in contributing to
the project should be able to provide
over 10 hours of speech recordings
with transcriptions and more than
200 sentences of written text, along
with translated sentences.

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The work consists of integrating low-
resource language datasets into
speech recognition and machine
translation (MT) models. In return,
collaborators will have the opportunity
to work directly with Meta’s research
teams, access technical workshops, and
learn how to leverage the resulting
open-source models. As part of the No
Language Left Behind (NLLB) project,
launched in 2022, Meta began
collaborating with UNESCO and
Hugging Face on an open-source MT
engine. The resulting translation
interface was announced during the
United Nations General Assembly week
in September 2024.

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Meta also made the Meta Massively
Multilingual Speech (MMS) interface
available in Hugging Face to support
the same UNESCO program. For this
project, Meta’s own massively
multilingual/multimodal translation
models support transcription for over
1,000 languages and are capable of
zero-shot speech recognition.
In the same partner program
announcement, Meta unveiled the
BOUQuET open-source machine
translation benchmark. This is a standard
seven-language evaluation tool intended
to help evaluate AI translation for
massively multilingual text-to-text
machine translation systems.

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A few weeks before this latest
announcement, the FAIR team
published in January 2025 an update in
the Nature journal about the
SeamlessM4T system, a set of models
capable of automatic speech
recognition (ASR), text-to-text
translation (T2TT), speech-to-text
translation (S2TT), text-to-speech
translation (T2ST), and speech-to-
speech translation (S2ST).
Meta also stated that with these projects,
“ultimately, our goal is to create
intelligent systems that can understand
and respond to complex human needs,
regardless of language or cultural
background.”

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