RSS
Логотип
Баннер в шапке 1
Баннер в шапке 2

CST innovation

Company

Information Technology
Russia


Top managers:
Aleksey Vladimirovich Yakovlev. 2
LLC CST innovation is a participant and holder of a grant from the Skolkovo Innovation Center, a subsidiary of the Center for Speech Technologies. "CST innovation" is active in the field of contactless biometrics. As part of Skolkovo, the company is developing a universal multimodal biometric platform for building systems used in the field of state and corporate security. The systems are based on new methods for recognizing audiovisual human images and the principles of artificial intelligence. Biometric solutions "CST innovation" are intended for implementation in the Russian and global market.

Owners:
Speech Technology Center Group (Speech Technology Center)

Content

Owners

+ Rosneft of the Tax Code
+ Nowfinteh
+ Oleg Mikhailovich Vaksman

2017

Grant for 270 million rubles for the development of the technology of analysis of the sound environment

On December 7, 2017, the CST innovation company received a grant of 270 million rubles from the National Technology Initiative (NTI). These funds will be used to develop the technology of analyzing the sound environment using artificial intelligence (AI), the Vedomosti newspaper writes, citing representatives of the CST innovations the state program.

We are talking about a technology called "Neurouho," which allows devices to recognize sounds and, in the presence of uncharacteristic noise (for example, with excessive hum at the enterprise), send notifications or control video cameras.

Russian developer of biometrics "CST innovation" attracted 270 million rubles from the state for a sound analysis system using AI

In addition, the developers promise to teach the system to determine gender and age by a person's voice. According to KPMG Nikolai Legkodimov, partner of the audit company, other similar systems do not have such a function.

The cost of the entire project is 390 million rubles. NTI allocated money subject to 30 percent private co-financing. 120 million rubles will be invested in the technology by the Center for Speech Technologies (CST; owner of "CST innovation"). It is assumed that the development will be able to pay off by 2022. And in another two years, the company expects revenue of 2 billion rubles.

According to Denis Filippov, head of the voice technology and product development department at Yandex, NTI money will be enough to create a prototype, and additional funds will be required for the industrial implementation of the technology.

Managing Director of Skolkovo Ventures Vladimir Sakovich says that state support can help technologies such as Neurouho quickly penetrate the public sector and the markets where they will be in demand.

The CST say that voice biometrics can come in handy in safe cities, robotics and smart homes, and workers in noisy industries will be warned of dangers.[1]

2016

CST received 120 million from FRP for facial recognition system

The company "CST innovation" from will receive a loan of 122.4 million rubles from the Industrial Development Fund (FRP) under the Ministry of Industry and Trade. The funds will be used to create a software and hardware complex for intelligent video processing of the CST: SmartTracker.

The total cost of the project will be 255.8 million rubles, that is, a preferential loan to the FRP will cover half of the costs. The loan is issued in connection with the need for import substitution, its conditions correspond to the program "Development Projects." With the specified loan amount and the total project budget, this means the accrual of 5% per annum and repayment within five years.

At the same time, the target sales volume of new products is at least 50% of the loan amount per year, starting from the second year of serial production.


Loan program for 2.1 billion rubles

The provision of funds to the CST innovation company is part of a financing program consisting of 9 concessional loans to import substitution projects from the FRP. In total, the Expert Council of the FRP allocated 2.1 billion rubles for this program. At the same time, the total cost of 9 approved projects exceeds 7.9 billion rubles. The fund claims that the issuance of these loans will attract 5.8 billion additional funds to the real sector of the economy.

Method for Highlighting Connected Word Usage Contexts

The CST innovation company (a group of CST companies), with the support of the Ministry of Education and Science of the Russian Federation, announced in April 2016 a method for highlighting coherent contexts of word use, focused on working with live unprepared (spontaneous) speech. The new method will be used in such CST speech analytics tools as the "clustering module" and the "automatic annotation module."

The method is based on big data technologies () big data and modern methods (machine learning machine learning) in combination with deep linguistic and semantic analysis of speech.

The problem of "understanding" speech (voice message and/or large volume of voice data) is especially acute in large contact centers that process information in constant mode and large volumes. That is why the main potential consumers of systems that automatically highlight connected contexts (logical structures, "situations") of certain words significant for analysis are analytical services of the CC and technical support services of state and commercial structures.

The purpose of highlighting contexts in large data sets is to take into account information directly related to the target word and not include irrelevant information in the context. Highlighting coherent word contexts greatly simplifies the work of analysts, allowing them to automatically solve such problems as:

  • analysis of the use of keywords (people, organizations, geographical objects) in the text and/or speech;
  • identification of contexts of use of key (significant) words in dialogues;
  • drafting a text annotation (informative squeeze) of the text and/or speech;
  • automatic generation of thematic cluster headers, etc.

Источник — «https://tadviser.com/index.php/Company:CST_innovation»

Шестерня

The site content is translated by machine translation software powered by PROMT. The machine-translated articles are not always perfect and may contain errors in vocabulary, syntax or grammar. Read original article

If you find inaccuracies or errors in the results of machine translation, please write to editor@tadviser.ru. We will make every effort to correct them as soon as possible.

How to create a "smart plant": Key characteristics of a modern digital enterprise
Model Studio CS: How to use BIM to give new impetus to the development of the fuel and energy complex