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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 .
On February 15, 2024, OpenAI first previewed Sora by releasing multiple clips of high-definition videos that it created, including an SUV driving down a mountain road, an animation of a "short fluffy monster" next to a candle, two people walking through Tokyo in the snow, and fake historical footage of the California gold rush, and stated that ...
Gen-2 is a multimodal AI system that can generate novel videos with text, images or video clips. The model is a continuation of Gen-1 and includes a modality to generate video conditioned to text. Gen-2 is one of the first commercially available text-to-video models. [31] [32] [33] [34]
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.
A short animation showing kinetic typography. Kinetic typography—the technical name for "moving text"—is an animation technique mixing motion and text to express ideas using video animation. This text is presented over time in a manner intended to convey or evoke a particular idea or emotion.
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