Neural Network to Change Background in Any Image

Massachusetts Institute of Technology researchers had created convinient image editor, based on AI
23 August 2018   416

Researchers from the Massachusetts Institute of Technology (MIT) presented an algorithm for a convolutional neural network, which automatically transfers objects from one image to another. In this case, the user does not need to select parts of the image or define their boundaries. This is reported by The Next Web.

The editor, called Semantic Soft Segmentation (SSS), divides objects and background into different segments. The system analyzes the color, transparency and texture of the edges of objects. It takes into account the semantic proximity of the pixels: they can belong to two objects simultaneously. As a result, on a new background, the objects look clear and without torn edges. The algorithm processes one image on average in 4 minutes.

In August 2018, the author of the blog, AI Weirdness told about the generative-controversial neural network AttnGAN, which draws images by text description. The problem with the algorithm is that it requires too precisely defined picture parameters and sometimes can not determine the boundaries of objects.

Microsoft to Use AI to Create Human Voice

Synthetic voice is nearly indistinguishable from recordings of people
27 September 2018   449

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.