Most speech-to-speech translation systems use text as an intermediate mode. So how do you build an automated translator for a language that has no standard written form? A new approach trained neural networks to translate a primarily oral language.
Most speech-to-speech translation systems use text as an intermediate mode. So how do you build an automated translator for a language that has no standard written form? A new approach trained neural networks to translate a primarily oral language.
Sentence pairs that have equivalent meanings in different languages — typically used to train machine translation systems — have been available in sufficient quantities for only around 100 languages. New work doubled that number and produced a more capable model.
Sentence pairs that have equivalent meanings in different languages — typically used to train machine translation systems — have been available in sufficient quantities for only around 100 languages. New work doubled that number and produced a more capable model.
In spoken conversation, people naturally take turns amid interjections and other patterns that aren’t strictly verbal. A new approach generated natural-sounding audio dialogs without training on text transcriptions that mark when one party should stop speaking and the other should chime in.
In spoken conversation, people naturally take turns amid interjections and other patterns that aren’t strictly verbal. A new approach generated natural-sounding audio dialogs without training on text transcriptions that mark when one party should stop speaking and the other should chime in.
Text-to-image generators like DALL·E 2, Midjourney, and Stable Diffusion are winning art contests and worrying artists. A new approach brings the magic of text-to-image generation to video.
Text-to-image generators like DALL·E 2, Midjourney, and Stable Diffusion are winning art contests and worrying artists. A new approach brings the magic of text-to-image generation to video.
Vision Transformers (ViTs) are overtaking convolutional neural networks (CNN) in many vision tasks, but procedures for training them are still tailored for CNNs. New research investigated how various training ingredients affect ViT performance.
Vision Transformers (ViTs) are overtaking convolutional neural networks (CNN) in many vision tasks, but procedures for training them are still tailored for CNNs. New research investigated how various training ingredients affect ViT performance.
A CLIP model whose weights were the mean of an ensemble of fine-tuned models performed as well as the ensemble and better than its best-performing constituent.
A CLIP model whose weights were the mean of an ensemble of fine-tuned models performed as well as the ensemble and better than its best-performing constituent.
Vision models can be improved by training them on several altered versions of the same image and also by encouraging their weights to be close to zero. Recent research showed that both can have adverse effects that may be difficult to detect.
Vision models can be improved by training them on several altered versions of the same image and also by encouraging their weights to be close to zero. Recent research showed that both can have adverse effects that may be difficult to detect.
Regulators are forcing Meta (formerly Facebook) to display certain advertisements more evenly across its membership. The United States government compelled Meta to revise its ad-placement system to deliver ads for housing to members regardless of their age, gender, or ethnicity.
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