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Meta's machine translation journey

#artificialintelligence

There are around 7000 languages spoken globally, but most translation models focus on English and other popular languages. This excludes a major part of the world from the benefit of having access to content, technologies and other advantages of being online. Tech giants are trying to bridge this gap. Just days back, Meta announced that it plans to bring out a Universal Speech Translator to translate speech from one language to another in real-time. This announcement is not surprising to anyone who follows the company closely. Meta has been devoted to bringing innovations in machine translations for quite some time now.


The first AI model that translates 100 languages without relying on English data

#artificialintelligence

Facebook AI is introducing, M2M-100 the first multilingual machine translation (MMT) model that translates between any pair of 100 languages without relying on English data. When translating, say, Chinese to French, previous best multilingual models train on Chinese to English and English to French, because English training data is the most widely available. Our model directly trains on Chinese to French data to better preserve meaning. It outperforms English-centric systems by 10 points on the widely used BLEU metric for evaluating machine translations. M2M-100 is trained on a total of 2,200 language directions -- or 10x more than previous best, English-centric multilingual models.


Behind No language Left Behind

#artificialintelligence

What if you didn't need English to translate? Meta's new and improved open source AI model'NLLB-200' is capable of translating 200 languages without English! "Communicating across languages is one superpower that AI provides, but as we keep advancing our AI work it's improving everything we do--from showing the most interesting content on Facebook and Instagram, to recommending more relevant ads, to keeping our services safe for everyone", says Mark Zuckerberg, CEO, Meta. Accessibility through language ensures that the benefits of the advancement of technology reach everyone, no matter what language they may speak. Tech companies are assuming a proactive role in attempting to bridge this gap.


Meta wants to build a universal language translator

Engadget

During an Inside the Lab: Building for the metaverse with AI livestream event on Wednesday, Meta CEO Mark Zuckerberg didn't just expound on his company's unblinking vision for the future, dubbed the Metaverse. He also revealed that Meta's research division is working on a universal speech translation system that could streamline users' interactions with AI within the company's digital universe. "The big goal here is to build a universal model that can incorporate knowledge across all modalities... all the information that is captured through rich sensors," Zuckerberg said. "This will enable a vast scale of predictions, decisions, and generation as well as whole new architectures training methods and algorithms that can learn from a vast and diverse range of different inputs." Zuckerberg noted that Facebook has continually striven to develop technologies that enable more people worldwide to access the internet and is confident that those efforts will translate to the Metaverse as well.


CoVoST V2: Expanding the largest, most diverse multilingual speech-to-text translation data set

#artificialintelligence

CoVoST V2 expands on our CoVoST data set, a speech-to-text translation (ST) corpus targeted at multilingual translation. This new release makes available the largest multilingual ST data set to date. CoVoST V2 will facilitate translating 21 languages into English, as well as English into 15 languages. In order to support wider research and applications in multilingual speech translation, we have released CoVoST V2 as free to use via a Creative Commons (CC0) license. Developed in 2019, the initial version of CoVoST used Mozilla's open source Common Voice database of crowdsourced voice recordings to create a corpus for translating 11 languages into English, with diverse speakers and accents.