The researchers’ system extracted a large number of vocal characteristics, such as “prosodic features,” which include the rhythm, intensity, rate, and frequency of speech. Facial features were extracted holistically. Then, the researchers trained the system on several short video samples of individuals showing different emotions, from which it connected certain features with emotions.