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YouTube now lets you watch auto-synced content in your own language

YouTube continues to improve its automatic syncing feature to make it easier for viewers to watch videos in languages ​​they actually understand. Auto-sync uses AI to translate the spoken audio of a video and replace it with a dubbed version in another language.

The feature now supports 27 languages ​​and viewers can set a preferred language in YouTube Settings. If a dubbed version is available, YouTube will automatically provide it in the selected language. So if there’s a video in another language, YouTube wants it to feel immediately accessible when you press play.

YouTube makes auto-dubs sound more natural

YouTube says it knows that dubbing can feel uncomfortable if it sounds robotic or out of sync. To address this issue, the company introduced Expressive Speech, a feature designed to preserve tone, emotion, and tempo in translated audio.

It is currently available for all YouTube channels in English, French, German, Hindi, Indonesian, Italian, Portuguese and Spanish. Additional languages ​​are expected later.

The platform is also testing a Lip Sync pilot that subtly adjusts a speaker’s lip movements to better match the translated sound. This makes synchronized videos feel closer to the original, especially for viewers who find mismatched audio and visual content distracting.

Auto-dubs are generated automatically, but the creators are not bound to them. You can turn off auto-dubbing completely or upload your own synced versions if you prefer more control.

YouTube also uses automatic intelligent filtering to avoid dubbing content that doesn’t make sense when translated, such as pure music videos or silent vlogs.

However, YouTube admits that automatic syncs can still contain errors, often due to poor voice recognition or unclear audio. The company says these systems will be improved over time as more feedback is received.

Aside from automatic syncing, YouTube is also embracing AI-driven personalization through its Recap feature, which assigns a personality to users based on their watch history, adding another layer to content understanding and presentation.

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