Accenture Global Solutions Limited

Misram LLC

Accenture Global Services Gmbh

Constantine T Boyadjiev

Rajarathnam Chandramouli

Koduvayur P Subbalakshmi

Zongru Shao

Michael Evan Wendt

Joshua Patterson

Paul Justin Mahler

A machine learning multi-dimensional acoustic feature vector authentication system, according to an example of the present disclosure, builds and trains multiple multi-dimensional acoustic feature vector machine learning classifiers to determine a probability of spoofing of a voice. The system may extract an acoustic feature from a voice sample of a user. The system may convert the acoustic feature into multi-dimensional acoustic feature vectors and apply the multi-dimensional acoustic feature vectors to the multi-dimensional acoustic feature vector machine learning classifiers to detect spoofing and determine whether to authenticate a user.

Machine learning for authenticating voice

According to an embodiment, a natural language processing artificial intelligence network and data security system determines an emotions model for one or more users from electronic natural language interactions of the users. The system includes a natural language processing decoder to determine textual features from the electronic natural language interactions that may be indicative of emotional states of the users. They system includes an emotions model encoder that generates an emotions model based on the emotional states of the users in the electronic natural language interactions retrieved from the data storage. The system also includes an artificial intelligence network and data security subsystem. The artificial intelligence network and data security subsystem may use the emotions model as a primitive for artificial intelligence based tasks including computer system security, network security, data security, proactive monitoring and preventive actions, that are moderated using the context provided by the emotional state of a user.

Natural language processing artificial intelligence network and data security system

A network security system detects anomalous network device behavior associated with a network device in a group of similar network devices based on baseline network device behavior determined for the group. A graphical visualization may be generated to analyze the groups.

Network security

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Jersey City, NJ, United States of America

Constantine T Boyadjiev