GVC Emotion Recognition
In many GVC applications the first step of the process is emotion recognition: the user speaks for a few seconds, and the GVC Emotion Recognition algorithm measures hundreds of acoustic properties of the user’s voice and distills from these cues an assessment of the user’s emotional state.
What are the acoustic cues?
The acoustic cues that we measure are numerous: static and dynamic properties of pitch, intensity, resonances, dullness, sharpness, softness, tempo, and phrasing
What is the immediate use of good emotion recognition?
An app that understands how you are currently feeling is capable of interacting with you in a much more natural and harmonious way than all those apps that stay ignorant of your mood. This has immediate consequences in Robotics.
What else can we expect from having good emotion recognition?
We can feed the results from our emotion recognition algorithm into algorithms that choose an appropriate feedback to the user. As GVC we are primarily interested in kinds of feedback that improve the user’s performance and quality of life.