The technology is an integrated solution incorporating the retrievable personality for multimodal emotion sensing for spoken services. This framework provides a real-world flexibility that enables the estimation of the target speaker emotion states without manual personalization.

When considering individuality in advancing emotion recognition, better modeling individual differences of human emotion expression is key. Our algorithm computes an unsupervised individual spaceachieves the best accuracy in the emotion benchmark. The work is published in the flagship conferences on affective computing (ACII2019)the worlds largest speech technology (INTERSPEECH2019).

User interface using speech technology will benefit from such a technology (SIRI, Alexa). Other applications can be found in customer care center analytics, remote human resource recruitment,even affect disorder health application.