MIT Researchers Use Wearable, AI To Detect Conversational Tone

Researchers with MIT's Computer Science and Artificial Intelligence Laboratory have combined AI with a concept wearable from Samsung called the "Simband" to detect conversational tones. The wearable combines multiple sources of data in an attempt to detect intention and emotional state.

It uses movement, heart rate, blood flow, blood pressure, skin temperature, and audio data to figure out what someone is feeling.

[The] algorithm's findings align well with what we humans might expect to observe. For instance, long pauses and a monotonous vocal tones were associated with sadder stories, while more energetic, varied speech patterns were associated with happier ones. In terms of body language, sadder stories were also strongly associated with increased fidgeting and cardiovascular activity, as well as certain postures like putting one's hands on one's face. - MIT

Compared to existing ways of detecting emotion and tone, this setup is 7.5% more accurate.