Accenture Corporation

Accenture Global Services Gmbh

Valery A Petrushin

Anatole Vitaly Gershman

Gang Wei

A computer system monitors a conversation between an agent and a customer. The system extracts a voice signal from the conversation and analyzes the voice signal to detect a voice characteristic of the customer. The system identifies an emotion corresponding to the voice characteristic and initiates an action based on the emotion. The action may include communicating the emotion to an emergency response team, or communicating feedback to a manager of the agent, as examples.

Detecting emotion in voice signals in a call center

A system, method and article of manufacture are provided for detecting emotion using statistics. First, a database is provided. The database has statistics including human associations of voice parameters with emotions. Next, a voice signal is received. At least one feature is extracted from the voice signal. Then the extracted voice feature is compared to the voice parameters in the database. An emotion is selected from the database based on the comparison of the extracted voice feature to the voice parameters and is then output.

A system for a community of multimedia agents (COMMA) is provided comprising an Agent Library and a Development Environment. The former comprises one or more multimedia agents contributed for use as components when developing more sophisticated systems. All contributed multimedia agents are provided in executable or object code format only to protect intellectual property rights of contributors. The Development Environment allows multimedia agents to be presented to users and allows users to build more sophisticated systems by combining the multimedia agents. The Development Environment also handles the coordination of agent execution. Results generated by the agents are visualized in the Development Environment to facilitate comparison of agent performance. Specifications based on the industry standard are provided for agents' inputs and outputs that facilitate communication among agents and allow the construction of hierarchies of agents. In this manner, the community fosters collaboration between researchers.

Community of multimedia agents

A system and method are provided for detecting emotional states using statistics. First, a speech signal is received. At least one acoustic parameter is extracted from the speech signal. Then statistics or features from samples of the voice are calculated from extracted speech parameters. The features serve as inputs to a classifier, which can be a computer program, a device or both. The classifier assigns at least one emotional state from a finite number of possible emotional states to the speech signal. The classifier also estimates the confidence of its decision. Features that are calculated may include a maximum value of a fundamental frequency, a standard deviation of the fundamental frequency, a range of the fundamental frequency, a mean of the fundamental frequency, and a variety of other statistics.

Detecting emotions using voice signal analysis

A system, method and article of manufacture are provided for managing voice messages based on emotion characteristics of the voice messages. First, a plurality of voice messages that are transferred over a telecommunication network are received. Thereafter, such voice messages are stored on a storage medium. An emotion associated with voice signals of the voice messages is then determined. The voice messages are organized based on the determined emotion. Access to the organized voice messages is then permitted.

Voice messaging system that organizes voice messages based on detected emotion

A system, method and article of manufacture are provided for detecting nervousness in a voice in a business environment to help prevent fraud. First, voice signals are received from a person during a business event. The voice signals are analyzed during the business event to determine a level of nervousness of the person, which is then output before the business event is completed. A degree of certainty as to the level of nervousness of the person may be output to assist one searching for fraud in making a determination as to whether the person was speaking fraudulently. Optionally, the level of nervousness of the person may be output in real time. As another option, an alarm may be set off when the level of nervousness goes above a predetermined level.

System, method and article of manufacture for a voice analysis system that detects nervousness for preventing fraud

A voice signal and an emotion associated therewith is provided. Then, the emotion associated with the voice signal is determined in an automated manner and subsequently stored. Next, a user determined emotion associated with the voice signal is determined by a user and received. The automatically determined emotion with the user determined emotion are then compared.

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Arlington Heights, IL, United States of America

Valery A Petrushin