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A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .
The features include an AI image generation tool which converts text into images, as well as a background eraser to erase unwanted objects and replace the background. It also includes image filters like blur, retro, VHS, and Y2K. The apps include: Picsart Photo & Video Editor - a photo and video editing app with tools to add filters and various ...
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [ 7 ] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [ 5 ]
Apps such as textPlus and WhatsApp use Text-to-Speech to read notifications aloud and provide voice-reply functionality. Google Cloud Text-to-Speech is powered by WaveNet, [5] software created by Google's UK-based AI subsidiary DeepMind, which was bought by Google in 2014. [6] It tries to distinguish from its competitors, Amazon and Microsoft. [7]
Dream Machine is a text-to-video model created by Luma Labs and launched in June 2024. It generates video output based on user prompts or still images. Dream Machine has been noted for its ability to realistically capture motion, while some critics have remarked upon the lack of transparency about its training data.
Speechify is a mobile, Chrome extension and desktop app that reads text aloud using a computer-generated text to speech voice. [1] [2] [3]The app also uses optical character recognition technology to turn physical books or printed text into audio which can be played in your own voice or in that of a celebrity.
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