Abstract: An automated emotional recognition system is adapted to determine emotional states of a speaker based on the analysis of a speech signal. The emotional recognition system includes at least one server function and at least one client function in communication with the at least one server function for receiving assistance in determining the emotional states of the speaker. The at least one client function includes an emotional features calculator adapted to receive the speech signal and to extract therefrom a set of speech features indicative of the emotional state of the speaker. The emotional state recognition system further includes at least one emotional state decider adapted to determine the emotional state of the speaker exploiting the set of speech features based on a decision model. The server function includes at least a decision model trainer adapted to update the selected decision model according to the speech signal.

Abstract: An automated emotional recognition system is adapted to determine emotional states of a speaker based on the analysis of a speech signal. The emotional recognition system includes at least one server function and at least one client function in communication with the at least one server function for receiving assistance in determining the emotional states of the speaker. The at least one client function includes an emotional features calculator adapted to receive the speech signal and to extract therefrom a set of speech features indicative of the emotional state of the speaker. The emotional state recognition system further includes at least one emotional state decider adapted to determine the emotional state of the speaker exploiting the set of speech features based on a decision model. The server function includes at least a decision model trainer adapted to update the selected decision model according to the speech signal.

Abstract: An automated emotional recognition system includes an emotional state classifier adapted to receive, during an operative phase, an input information stream with embedded information related to emotional states of a person, and to generate a succession of emotional state indications derived from the input information stream. The emotional recognition system further includes a post-processing function, configured to receive at least two emotional state indications of the succession and, for each of said at least two emotional state indications, determine a corresponding emotional state representation in an emotional state representation system. The post-processing function is further configured to combine the emotional state representations of the at least two emotional state indications to obtain an output emotional state indication.