Zeroing In On Anger

Rip-roaring mad? Or cool as a cucumber? In sifting through billions of voice messages, analysts are more interested in angry than in calm speakers.

A decision-tree classifier like this one is being tweaked to assess a person's state of mind. It classifies speech by parameters like pitch, vowel duration, and average energy (loudness), normalized for the speaker, word content, and channel. It also checks whether pitch falls steeply at the end of a sentence [red boxes].

At each branch, the classifier assigns probabilities that someone is angry, or calm, in the light of empirical experience [yellow boxes]. Presented with a high-pitched utterance, the classifier assigns a probability of 0.62 to anger—hardly definitive.

So if a further test finds a high maximum vowel duration, a probability of 0.91 for anger is assigned—pretty conclusive. If the vowel duration is low, then the probability of anger is only 0.54, so a third test is applied. And so on.