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  2. Sora (text-to-video model) - Wikipedia

    en.wikipedia.org/wiki/Sora_(text-to-video_model)

    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 ]

  3. BBC Sounds launches trial of generative AI-powered subtitles

    www.aol.com/bbc-sounds-launches-trial-generative...

    A range of audio programmes will have transcripts produced using an artificial intelligence tool as part of a three-month trial of the technology. BBC Sounds launches trial of generative AI ...

  4. Comparison of subtitle editors - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_subtitle_editors

    SRT, SSA, SBV, VTT, DFXP, ITT, SCC and CAP formats. [2] Cloud platform with subtitle editor and workflow tools for collaborative captioning and subtitling, including making corrections to machine-generated captions. Add-ons include automatic speech recognition. Gnome Subtitles: GPL Linux Yes

  5. Aegisub - Wikipedia

    en.wikipedia.org/wiki/Aegisub

    Aegisub is a subtitle editing application. It is the main tool used for fansubbing, the practice of creating or translating unofficial subtitles for visual media by fans. [3] It is the successor of the original SubStation Alpha and Sabbu. Aegisub's design emphasizes timing, styling of subtitles, and the creation of karaoke videos.

  6. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Video generated by Sora with prompt Borneo wildlife on the Kinabatangan River. Generative AI trained on annotated video can generate temporally-coherent, detailed and photorealistic video clips. Examples include Sora by OpenAI, [12] Gen-1 and Gen-2 by Runway, [76] and Make-A-Video by Meta Platforms. [77]

  7. Text-to-video model - Wikipedia

    en.wikipedia.org/wiki/Text-to-video_model

    There are several architectures that have been used to create Text-to-Video models. Similar to Text-to-Image models, these models can be trained using Recurrent Neural Networks (RNNs) such as long short-term memory (LSTM) networks, which has been used for Pixel Transformation Models and Stochastic Video Generation Models, which aid in consistency and realism respectively. [31]