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Meta launches AI translation suite Seamless Communication

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2023-12-04 17:23:20652browse

Meta recently released Seamless Communication, an AI translation suite. This suite contains four AI models. Meta claims that this AI suite can accurately reproduce the speaker's emotions, and can achieve simultaneous interpretation capabilities with only a two-second delay, while also supporting input in nearly a hundred languages

It is reported that Seamless Communication is a research result published by Meta to celebrate the 10th anniversary of the founding of its own AI research organization "Fundamental AI Research".

Meta 推出 AI 翻译套件 Seamless Communication

Meta said that the kit includes the "second-generation SeamlessM4T model" for accelerating translation, the interpretation model "Seamless Expressive", the simultaneous translation model "Seamless Streaming", and the comprehensive model "Seamless". The following is relevant information compiled by IT House:

SeamlessM4T model claims to be able to automatically associate possible subsequent texts during the translation process based on the user's spoken content to speed up translation

Meta 推出 AI 翻译套件 Seamless Communication

Meta 推出 AI 翻译套件 Seamless Communication

Seamless Expressive is an interpretation model that is said to be able to solve the problem that traditional AI translation cannot grasp the user's intonation, pauses, and word emphasis. It can also retain the user's emotion, style, and style while maintaining translation quality. Speech speed, pauses and rhythm to bring more emotional information to translated content

Seamless Streaming is a simultaneous interpretation model that focuses on providing speech and text translation with a 2-second delay, supporting real-time interpretation, speech-to-text translation (S2TT) and automatic speech recognition (ASR)

The comprehensive model Seamless integrates the above three language models to facilitate universal scenarios.

Meta 推出 AI 翻译套件 Seamless Communication

Currently, Meta has published the sample video on GitHub and the HuggingFace website. Interested friends can click here to view it.

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