Patent review : Detecting emotion in voice signals using correlation

The patent emphasises the implementation of a system for detection of emotions in a real time voice signal.

First, a database is provided. This includes statistics of human associations of voice parameters with emotions. Next, a voice signal is received. Minimum one feature is extracted from the voice signal. Then the extracted voice feature is correlated with the voice parameters in the database. An emotion is automatically selected from the database based on the correlated output of the extracted voice feature and the voice parameters and is then output.

     The feature that is extracted includes 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, a mean of a bandwidth , a standard deviation of energy, a speaking rate, a slope of the fundamental frequency, a maximum value of the energy, a range of the energy.

       The database includes probabilities of a particular voice feature being associated with an emotion. Preferably, the selection of the emotion from the database includes analyzing the probabilities and selecting the most probable emotion based on the probabilities. Optionally, the probabilities of the database may include performance confusion statistics. 

patent: US 7,940,914 B2