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# Meta Advances AI for Speech, Translation, and Brain Communication Research

**[Collections](https://daily.dev/sources/collections)** · 2 min read · 1 upvotes · 0 comments

## Summary

Meta and UNESCO have teamed up to advance AI for speech recognition and translation, focusing on underserved languages. The Language Technology Partner Program collects data from diverse communities, and Meta has released an open-source machine translation benchmark on Hugging Face. Additionally, Meta is researching decoding language from brain signals, which could aid non-invasive brain-computer interfaces. Meta's contributions aim to improve their products and support global AI research.

## Content

# Meta and UNESCO Collaborate to Enhance AI for Speech Recognition and Translation

Meta, in collaboration with UNESCO, has launched an ambitious program to improve AI technologies for speech recognition and translation by collecting diverse language data. The initiative aims to focus on underserved languages, which have been historically neglected in AI development. By doing so, the program hopes to enhance Meta's AI-powered assistant capabilities and translation features, ultimately making these tools more inclusive and effective.

A critical component of this initiative is the Language Technology Partner Program, which seeks to gather speech recordings and transcriptions from various language communities. Early partners of this program include regions like Nunavut in Northern Canada, emphasizing the focus on underrepresented languages.

In addition to data collection, Meta has released an open-source machine translation benchmark to evaluate the performance of translation models. This benchmark is accessible via Hugging Face, a popular platform among AI researchers and developers. The availability of this benchmark supports the broader AI research community in developing more accurate and efficient language translation models.

Furthermore, Meta's AI research lab, in collaboration with the Basque Center, has made significant progress in decoding language from brain signals. This research has potential implications for developing non-invasive brain-computer interfaces, particularly for individuals who have lost their ability to speak. The study uses MEG signals to track how the brain converts thoughts into motor actions, providing insights into the dynamic neural codes for language representation.

Meta's contribution to this field is not solely for philanthropic purposes, though. Improved AI capabilities for speech and translation can significantly benefit Meta's products and services. By better handling non-English content and supporting a wider array of languages, Meta’s platforms can better serve their global user base.

Moreover, Meta is contributing $2.2 million to support further research in this area, underlining their commitment to advancing understanding in human communication and AI's role in it. The open-source nature of the AI tools and research ensures that the developments can benefit a broad range of applications, including healthcare innovations and tackling global challenges.

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Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#speech-recognition](https://daily.dev/tags/speech-recognition), [#brain-computer-interface](https://daily.dev/tags/brain-computer-interface)

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