Automatically Measuring Emotion from Speech: New Methods to Move from the Lab to the Real World – with Undergraduate Researchers!

Abstract Part 1: Emotion has intrigued researchers for generations. This fascination has permeated the engineering community, motivating the development of affective computational models for classification. However, human emotion remains notoriously difficult due to real world variability, contextual differences, and many other factors.  Yet, this research also holds promise: if we can automatically measure emotion as individuals go about their days, we will be better positioned to understand the link between patterns in emotion expression and underlying health conditions.  In the first part of this seminar, I will present new findings in this area. 

Abstract Part 2: As academic researchers, one of our mandates is to train the next generation of researchers, providing guidance, training, and opportunities.  However, due to the complexity of many of our problem domains (see abstract part 1) it can be daunting to figure out how to productively engage with first time undergraduate researchers and how to provide them with the research opportunities that will start their research career.  In the second part of this seminar, we will collectively brainstorm and discuss how we can increase access and decrease gatekeeping in research by sharing effective practices to support new researchers, particularly those just beginning their research careers. 

Zoom information will be sent to e-HAIL members.