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  2. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    They fail, however, when the text type is less structured, which is also common on the Web. Recent effort on adaptive information extraction motivates the development of IE systems that can handle different types of text, from well-structured to almost free text -where common wrappers fail- including mixed types. Such systems can exploit ...

  3. Avidemux - Wikipedia

    en.wikipedia.org/wiki/Avidemux

    Avidemux can also insert audio streams into a video file (an action known as multiplexing or "muxing") or extract audio streams from video files (an action known as "demuxing"). An integral and important part of the design of the program is its project system, which uses the SpiderMonkey JavaScript engine. Whole projects with all options ...

  4. 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]

  5. Why AI-generated audio is so hard to detect - AOL

    www.aol.com/news/why-ai-generated-audio-hard...

    There’s a glut of companies that offer text-to-speech services that mimic real voices for free or cheap. “If you simply search AI-based fake speech, you will get tens of searches right away ...

  6. MediaHuman Audio Converter - Wikipedia

    en.wikipedia.org/wiki/MediaHuman_Audio_Converter

    MediaHuman Audio Converter is a freeware audio conversion utility developed by MediaHuman Ltd. The program is used to convert across different audio formats, [1] split lossless audio files using CUE and extract audio from video files. The app can be run on Mac [2] starting from OS X 10.6 and on Windows XP and higher. [3]

  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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