You BEEP Machine - Emotion in AutomaticSpeech Understanding

In this paper we report on rst experiments for the detection of emotion and the use of this information in a complex speech understanding system like Verbmobil. We do not look at lexical information like swear words but rather try to nd emotional utterances with the use of acoustic prosodic cues. We only want to classify angry versus neutral speaking style. 20 speakers were asked to produce 50 neutral and 50 angry utterances. With this data set we created one training set and two test sets. One test set with seen speakers, but new turns, the other with unseen speakers, but seen turns. Each word of the emotional utterances was labeled as belonging to the class "emotional", each word in the neutral utterances as belonging to the class "neutral". For each word 276 prosodic features were calculated and multi layer perceptrons were trained for the two classes. We achieved a precision of 87% and a recall of 92% for the one test set and 94% respectively 84% for the other (precision respectively recall), when classifying turns as being either emotionally or neutral.