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The global voice biometrics market size to grow from USD 1.1 billion in 2020 to USD 3.9 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 22.8% during the forecast period.
The services segment is expected to grow at a higher CAGR during the forecast period
The global voice biometrics market has been segmented by component. The component segment is further categorized into solutions and services. Based on the solutions segment, the market is divided into platform and software. The services segment is further divided into managed services and professional services. The services segment is anticipated to grow at a higher CAGR during the forecast period. The growth of the services segment is governed mainly by the complexity of operations and the surge in the deployment of voice biometrics solutions during the forecast period.
The services segment is expected to grow at a higher CAGR during the forecast period
The global voice biometrics market has been segmented by component. The component segment is further categorized into solutions and services. Based on the solutions segment, the market is divided into platform and software. The services segment is further divided into managed services and professional services. The services segment is anticipated to grow at a higher CAGR during the forecast period. The growth of the services segment is governed mainly by the complexity of operations and the surge in the deployment of voice biometrics solutions during the forecast period.
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Social media is increasingly used to spread fake news. The same problem can be found on the capital market - criminals spread fake news about companies in order to manipulate share prices. Researchers at the Universities of Göttingen and Frankfurt and the Jožef Stefan Institute in Ljubljana have developed an approach that can recognise such fake news, even when the news contents are repeatedly adapted. The results of the study were published in the
Journal of the Association for Information Systems.
In order to detect false information - often fictitious data that presents a company in a positive light - the scientists used machine learning methods and created classification models that can be applied to identify suspicious messages based on their content and certain linguistic characteristics. Here we look at other aspects of the text that makes up the message, such as the comprehensibility of the language and the mood that the text conveys, says Professor Jan