Detecting emotions using voice signal analysis

A system for classifying speech contained in telephone calls, the system comprising:

• a computer system comprising a central processing unit, an input device, at least one random access memory for storing data indicative of speech signals, and an output device;
• logic for receiving and analyzing speech signals of telephone callers;
• logic for dividing the speech signals of the telephone callers;
• logic for extracting at least one feature from the speech signals of the telephone callers;
• logic for calculating statistics of the speech of the telephone callers;
• logic for at least one neural network for classifying the speech of the telephone callers as belonging to at least one of a finite number of emotional states;
• and
• logic for storing the speech signals and the emotional states in a storage medium, in a manner to allow later retrieval of the stored speech signals and emotional states;
• logic for outputting an indication of the at least one emotional state of the telephone callers;
• wherein the logic for at least one neural network comprises at least one three-layer neural network;
• and
• further comprising logic for routing a call containing said speech signals to at least one predetermined location according to the at least one classified emotional state.

A method of recognizing emotional states in a voice of a telephone caller, the method comprising:

• providing a first plurality of voice samples;
• obtaining a second plurality of voice samples of a telephone caller, from a telephone call;
• identifying each sample of said pluralities of samples as belonging to a predominant emotional state;
• dividing each sample into at least one of frames, subframes, and segments;
• extracting at least one acoustic feature for each sample of the pluralities of samples;
• calculating statistics of the speech samples from the at least one feature;
• classifying an emotional state in the first plurality of samples with at least one neural network;
• training the at least one neural network to recognize an emotional state from the statistics by comparing the results of identifying and classifying for the first plurality of samples;
• classifying an emotion in the second plurality of voice samples obtained from a telephone call with the at least one trained neural network;
• storing the voice samples and the emotional states in a storage medium, in a manner to allow later retrieval of the stored voice samples and emotional states;
• outputting in a human-recognizable format an indication of the emotional state of the telephone caller;
• and
• routing the call containing said voice samples to at least one predetermined location according to the at least one classified emotional state.

A system for detecting emotional states of telephone callers from speech signals of telephone calls, the system comprising:

• a speech reception device;
• at least one computer connected to the speech reception device;
• at least one random access memory operably connected to the at least one computer;
• a computer program including at least one neural network for dividing the speech signals into a plurality of segments, and for analyzing the segments according to features of the segments to detect the emotional state in the speech signals, and storing the speech signals and the emotional states in a storage medium, in a manner to allow later retrieval of the stored speech signals and emotional states and outputting in a human-recognizable format an indication of the emotional state of the speech signals;
• an output device coupled to the computer for notifying a user of the emotional states of the telephone callers detected in the speech signals;
• wherein the at least one neural network comprises at least one three-layer neural network;
• and
• further comprising logic for routing a call containing said speech signals to at least one predetermined location according to the at least one classified emotional state.