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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 .
Sora is a text-to-video model developed by OpenAI. The model generates short video clips based on user prompts, and can also extend existing short videos. Sora was released publicly for ChatGPT Plus and ChatGPT Pro users in December 2024. [1] [2]
Tacotron employed an encoder-decoder architecture with attention mechanisms to convert input text into mel-spectrograms, which were then converted to waveforms using a separate neural vocoder. When trained on smaller datasets, such as 2 hours of speech, the output quality degraded while still being able to maintain intelligible speech, and with ...
Users will be able to generate videos up to 1080-pixel resolution up to 20 seconds long and in widescreen, vertical or square aspect ratios. OpenAI released its video-to-text model Sora Monday.
Text-to-video generation, such as text-to-video generators, generated videos etc. Pages in category "Text-to-video generation" The following 11 pages are in this category, out of 11 total.
In deep learning-keyed speech synthesis, spectrogram (or spectrogram in mel scale) is first predicted by a seq2seq model, then the spectrogram is fed to a neural vocoder to derive the synthesized raw waveform. By reversing the process of producing a spectrogram, it is possible to create a signal whose spectrogram is an arbitrary image.
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