Nemesysco’s SCA1 Automated “Emotional content” & Veracity call analyzer for multi- channel recording systems Targeted at government intelligence and Law.

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Presentation transcript:

Nemesysco’s SCA1 Automated “Emotional content” & Veracity call analyzer for multi- channel recording systems Targeted at government intelligence and Law enforcement organizations Based on Nemesysco’s proprietary security level technology (Layered Voice Analysis) Provided as a set of WIN COM objects designed for integration into existing SIGINT software systems.

Nemesysco’s SCA1 Automated “Emotional content” & Veracity call analyzer for multi- channel recording systems Highlights: Analysis of the emotional content of calls rather than the verbal / textual content. Analyzes the veracity of a speaker Flags calls defined as “emotionally interesting“ Uses a heuristic learning mechanism to learn the emotional make of “priority calls” and then find them within voice recording databases or in real time

SCA1 Applications General purpose recording analysis Detect/prioritize out of a mass of recordings the relevant calls that should be further reviewed Immediate veracity assessment layer of information for processing needs SCA1 can analyze up to 4 voice streams in a call (conference call)

SCA1 Applications Monitoring “assets’” emotional activity Identify “Keywords” or coded words by the assets’ emotional reactions surrounding the word Monitor changes in assets’ emotional profile during interactions with other conversation partners Continues Indications of increasing stress, excitement and energy levels over a period of time may suggest proximity to execution of a plan Gain knowledge about an asset’s likes and dislikes, emotional attachments and motivations

SCA1 Applications Counter-Intelligence Constantly monitor stress and other emotional variables in sensitive facilities and flag emotionally unique cases Veracity assessment Veracity level determination based on the intent of the monitored subject - A major advantage for any investigation / intelligence body. Data can be collected from most audio sources (phone conversations, radio broadcast, TV, etc.)

Example – online analysis The technology can be used in Real time as well as on pre- recorded data Is one participant misleading the other? Are they both acting to mislead you?

Example – offline processing Provides a comprehensive set of analysis parameters Explore and better understand the monitored subjects, their “Stressors” and “excitors”. 1 st line: Veracity Level 2 nd line: Emotional Energy 3 rd line: Happy/Sad/Angry 4 th line: Stress level 5 th line: Vocal Energy

Example – emotional profile Online emotional profile of the speaker: Blue: baseline values Red: current (real-time) value

Reports & LioNet acquisition LioNet is Nemesysco’s proprietary Learning Engine, designed for automated decision making based on continuous feedback input.

TECHNICAL ASPECTS

SCA1 - a possible system architecture SCA1 Server Mass Recording System

SCA1 Software Development Kit (SDK) SCA1 is designed as a set of WIN COM Objects that can be easily integrated into any existing monitoring/interception solution and silently analyze voice interactions between several parties. SCA1 can be used to scan ongoing calls or archived recordings, from almost any source (provided the sound quality is reasonable and the voices are not too distorted).

The SDK Components Call Controller Object Manages the whole analysis set and different channels of a single call, and segment, extract the emotional variables from the streaming voice data, and complete the standard analysis cycle, up to the generation of the SCA1 signature file. LioNet Object An adaptive heuristic statistical learning engine, designed to process Emotional Signatures generated by the SCA1 core. LioNet will quickly compare the new Emotional Signature with known/trained emotional structures to generate a “Priority Flag”. Data Aggregator Object Designed to process the statistical portion of SCA1’s signature file. NMS Decision Unit The Decision unit combines several LioNet objects and Data Aggregators to reach a final priority decision.

Implementation options SCA1 Post Processing server The base of the SCA1 system. Post processing posts receive pre-recorded files or streaming data from the recording/acquisition system and utilize the SCA1 to generate the emotion analysis and conversation signature. The conversation signature is then processed by the LioNet shared server to provide a priority flag for the call. The emotional signature, together with the priority flag, are then stored in a general database. Online analysis posts When immediate analysis of streaming data is required, the SCA1 SDK can be used to design an “SCA1 Online post” providing textual, graphical and numerical data for the operator in real-time. The textual messages describe the current emotional/veracity assessment and may vary from “Truth”, “Excitement” and “Subject not sure” to “Inaccuracy” and “False”. The online posts typically comprise few more elements such as database connectivity for analysis feedback and textual editors for analysis comments. Offline analysis posts Once pre-recoded material is identified as relevant or important, an “Offline post” may receive the file and perform a complete analysis on its content, to pinpoint emotionally “charged” or suspected portions. An offline post may also provide its data in textual, graphical and numerical forms. Both online and offline posts should connect to the LioNet database for training purposes of the system.

Thank you