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  2. SubRip - Wikipedia

    en.wikipedia.org/wiki/SubRip

    SubRip is a free software program for Microsoft Windows which extracts subtitles and their timings from various video formats to a text file. It is released under the GNU GPL . [ 9 ] Its subtitle format's file extension is .srt and is widely supported.

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

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

    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]

  4. Niconico - Wikipedia

    en.wikipedia.org/wiki/Niconico

    The first version of Niconico used YouTube as a video source. When the site grew, YouTube's server infrastructure strained due to increased traffic and bandwidth, leading YouTube to make a decision to block access from Niconico. As a result, Niconico ceased operations for two weeks. The site relaunched with an on-premises video server.

  5. WebVTT - Wikipedia

    en.wikipedia.org/wiki/WebVTT

    WebVTT (Web Video Text Tracks) is a World Wide Web Consortium (W3C) standard for displaying timed text in connection with the HTML5 <track> element.. The early drafts of its specification were written by the WHATWG in 2010 after discussions about what caption format should be supported by HTML5—the main options being the relatively mature, XML-based Timed Text Markup Language (TTML) or an ...

  6. List of YouTube features - Wikipedia

    en.wikipedia.org/wiki/List_of_YouTube_features

    Since June 2007, YouTube's videos have been available for viewing on a range of Apple products. This required YouTube's content to be transcoded into Apple's preferred video standard, H.264, a process that took several months. YouTube videos can be viewed on devices including Apple TV, iPod Touch and the iPhone. [108]

  7. Text-to-video model - Wikipedia

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

    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 .

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