Facebook to Create a Dataset to Train Dialogue AI

The dataset includes 5 million characters and 700 million dialogues
19 September 2018   229

Researchers from Facebook created a set of training data to improve the effectiveness of neural networks training, specializing in communicating with live users. It includes 5 million characters and 700 million dialogues.

Persona-based network architecture
Persona-based network architecture

In the basis of the software, developers have put a set of PERSONA-CHAT, developed jointly by Facebook experts and scientists from the Montreal Institute of Learning Algorithms. First of all, the increase in the volume of data is notable - the basic data-set contained only about a thousand personalities. But researchers are paying attention to a more important aspect. The PERSONA-CHAT content was created artificially, and the new set was formed on the basis of the Reddit user dialogues.

An interactive neural network, trained on a new set of data, leads more engaging dialogues than networks that did not have access to a collection of personalities. Moreover, the training of systems based on the characters is faster.

Choosing the right data set for learning artificial intelligence is one of the key tasks for developers. The accuracy and productivity of the software being created depends on it. In September 2018, Google in the test mode launched a special tool to find suitable collections.

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.