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  2. 7 Ways AI Can Create or Tweak Your Resume Before Your Next ...

    www.aol.com/lifestyle/7-ways-ai-create-tweak...

    Employers spend an average of six to seven seconds looking at a resume. So your resume needs to enable them to find key information quickly. 7 Ways AI Can Create or Tweak Your Resume Before Your ...

  3. 20 Productivity Tech & AI Tools Perfect for Freelancers

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    Skip to main content. Subscriptions; Animals

  4. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    Audio deepfake technology, also referred to as voice cloning or deepfake audio, is an application of artificial intelligence designed to generate speech that convincingly mimics specific individuals, often synthesizing phrases or sentences they have never spoken.

  5. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    A stack of dilated casual convolutional layers used in WaveNet [1]. In September 2016, DeepMind proposed WaveNet, a deep generative model of raw audio waveforms, demonstrating that deep learning-based models are capable of modeling raw waveforms and generating speech from acoustic features like spectrograms or mel-spectrograms.

  6. 15.ai - Wikipedia

    en.wikipedia.org/wiki/15.ai

    15.ai was a free non-commercial web application that used artificial intelligence to generate text-to-speech voices of fictional characters from popular media. [1] Created by an artificial intelligence researcher known as 15 during their time at the Massachusetts Institute of Technology, the application allowed users to make characters from video games, television shows, and movies speak ...

  7. Retrieval-based Voice Conversion - Wikipedia

    en.wikipedia.org/wiki/Retrieval-Based_Voice...

    Retrieval-based Voice Conversion (RVC) is an open source voice conversion AI algorithm that enables realistic speech-to-speech transformations, accurately preserving the intonation and audio characteristics of the original speaker.

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  9. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    For example, the set cover problem is a special case of submodular optimization, since the set cover function is submodular. The set cover function attempts to find a subset of objects which cover a given set of concepts. For example, in document summarization, one would like the summary to cover all important and relevant concepts in the document.

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