TY - JOUR
T1 - The MEI robot
T2 - Towards using motherese to develop multimodal emotional intelligence
AU - Lim, Angelica
AU - Okuno, Hiroshi G.
PY - 2014
Y1 - 2014
N2 - We introduce the first steps in a developmental robot called MEI (multimodal emotional intelligence), a robot that can understand and express emotions in voice, gesture and gait using a controller trained only on voice. Whereas it is known that humans can perceive affect in voice, movement, music and even as little as point light displays, it is not clear how humans develop this skill. Is it innate? If not, how does this emotional intelligence develop in infants? The MEI robot develops these skills through vocal input and perceptual mapping of vocal features to other modalities. We base MEI's development on the idea that motherese is used as a way to associate dynamic vocal contours to facial emotion from an early age. MEI uses these dynamic contours to both understand and express multimodal emotions using a unified model called SIRE (Speed, Intensity, irRegularity, and Extent). Offline experiments with MEI support its cross-modal generalization ability: a model trained with voice data can recognize happiness, sadness, and fear in a completely different modality - human gait. User evaluations of the MEI robot speaking, gesturing and walking show that it can reliably express multimodal happiness and sadness using only the voice-trained model as a basis.
AB - We introduce the first steps in a developmental robot called MEI (multimodal emotional intelligence), a robot that can understand and express emotions in voice, gesture and gait using a controller trained only on voice. Whereas it is known that humans can perceive affect in voice, movement, music and even as little as point light displays, it is not clear how humans develop this skill. Is it innate? If not, how does this emotional intelligence develop in infants? The MEI robot develops these skills through vocal input and perceptual mapping of vocal features to other modalities. We base MEI's development on the idea that motherese is used as a way to associate dynamic vocal contours to facial emotion from an early age. MEI uses these dynamic contours to both understand and express multimodal emotions using a unified model called SIRE (Speed, Intensity, irRegularity, and Extent). Offline experiments with MEI support its cross-modal generalization ability: a model trained with voice data can recognize happiness, sadness, and fear in a completely different modality - human gait. User evaluations of the MEI robot speaking, gesturing and walking show that it can reliably express multimodal happiness and sadness using only the voice-trained model as a basis.
KW - Cross-modal recognition
KW - emotion recognition
KW - gait
KW - gaussian mixture
KW - gesture
KW - motherese
KW - SIRE
KW - voice
UR - http://www.scopus.com/inward/record.url?scp=84903213220&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903213220&partnerID=8YFLogxK
U2 - 10.1109/TAMD.2014.2317513
DO - 10.1109/TAMD.2014.2317513
M3 - Article
AN - SCOPUS:84903213220
VL - 6
SP - 126
EP - 138
JO - IEEE Transactions on Cognitive and Developmental Systems
JF - IEEE Transactions on Cognitive and Developmental Systems
SN - 2379-8920
IS - 2
M1 - 6798757
ER -