Scientists to Create Deepfakes for Dancing

With help of artificial intelligence, fake dancing videos can now be created
28 August 2018   402

Four scientists from the University of California at Berkeley developed an algorithm that creates on the basis of a video with a dance a fake record on which another person performs the same movements. For deep processing, it requires a twenty-minute shooting at 120 frames per second.

The technology is based on an algorithm on generative-competitive neural networks. A separate subroutine processes pre-recorded video (source and target) and imposes motions on a simple figure - the frame of the human body.

AI Dancing
AI Dancing
AI Dancing
AI Dancing

Then the algorithm transfers professional movements to the record of amateur dance and "aligns" the final video so that the figure does not strongly "jerk" from frame to frame and the person was where he was supposed to.

Researchers admit that the synthesized video looks realistic though it is not devoid of artifacts: body parts sometimes tremble or even disappear, and some frames look blurred. In addition, the algorithm does not know how to handle the behavior of the tissue when a person moves, so people on the target video wear tight clothing that almost does not form wrinkles.

This type of video processing is called a "deep fake". In mid-August, 2018, experts from the Carnegie Mellon University presented Recycle-GAN, which is capable of recreating the facial expressions of one person on the face of another, modeling the blossoming of the flower and changing the weather on video recordings. A similar result is provided by the application FakeApp, released in January 2018, as well as the algorithms Face2Face and HeadOn.

Microsoft to Use AI to Create Human Voice

Synthetic voice is nearly indistinguishable from recordings of people
27 September 2018   457

Researchers from Microsoft recorded computer voice, imitating human speech. To overcome the difficulties of the traditional model, they used neural networks for speech synthesis. Microsoft promises to provide support for 49 languages ​​and the ability to create unique voices for the needs of companies in the near future.

Synthesis of speech with the help of neural networks involves comparing the stress and length (so-called prosody) of the speaker's speech units, as well as their synthesis into a computer voice. In systems of traditional speech synthesis, prosody is divided into acoustic and linguistic analysis, controlled by various models. As a result, the speech is noisy and indistinct. Representatives of Microsoft argue that in the model of neural synthesis two stages are combined into one, so the voice sounds like a real one.

The developers are convinced that the synthesis of speech with the help of neural networks will make it more natural to communicate with virtual interlocutors and assistants. Moreover, it will enable you to convert e-books into audiobooks and will allow you to change the scoring of built-in navigators.

Microsoft Neural TTS
Microsoft Neural TTS

Azure computing power is available for real-time use, and Azure Kubernetes is responsible for this. Simultaneous application of neural synthesis of speech together with traditional speaks about expansion and increase of availability of service. At the moment, there are a female voice named Jessa and a man named Guy.

Microsoft is competing in speech recognition and synthesis technologies with Google, which updated its services in late August 2018. Google Cloud announced the release of a stable API for the synthesis of speech Cloud Text-to-Speech with the experimental function of audio profiles and support for several new languages.