TECHNOLOGY
We have always wanted to have the ability to know if what someone tells us is true or not, to know how people realy feel regarding different issues.
The technology was originally invented in 1997 by Amir Liberman, and has been developed ever since in cooperation with experts from different relevant fields (psychology, criminology, phonetics, psychiatry, mathematics, and others).
The technology relies on a proprietary set of vocal parameters found through research to correlate with key human emotions, and on various combinations to identify misleading intentions in "real life" scenarios. These vocal parameters were identified from a bank of thousands of audio files taken in different languages and a host of settings, including police interrogations, call centers, and controlled experiments.
Layered Voice Analysis (LVA ™) is the core technology tailored to meet the needs of diverse professional users, from police investigations to security permits, from human resources screening tests to personality tests . Quality analysis of customer service in Call Centers to telemarketing actions.
In its Security applications, LVA technology allows us to know the mental and emotional state of the person being analyzed and thus to know what emotions intervene when speaking, and how these vary according to the topic that is touched in the conversation.
The technology identifies various types of stress levels, cognitive processes, and emotional reactions that are reflected in different subtle properties of the voice. This information provides knowledge about the way the subject thinks, what worries him, what excites him, what makes him afraid or embarrassed, what parts of his speech is uncertain, when he uses imagination instead of memory, when he repents if you have said something, which questions require your attention the most to answer and which topics are sensitive or dangerous questions for the speaker.
LVA uses a unique mathematical algorithm to detect different types of speech flow patterns and abnormalities and classify them in terms of stress, emotion, confusion, and other relevant emotional states, found through our 19 years of research highly correlated with these emotions.