I am very happy to introduce myself as a new Futures Initiative (FI) Fellow. As my first blog post (ever), I’d like to use this post to briefly introduce myself and to describe what I’ll be doing as a fellow.
First, a little about me…I am a PhD student in computational linguistics, which is a fancy way to say I am interested in language and computers. Specifically, when it comes to language, I am interested in what language can tell us about an individual’s emotions. I strongly believe that language can be and should be used as a diagnostic for assessing a person’s mental health and well-being. Language is complex and extremely informative. When I say language, I do not refer to only the words we use, but rather a more sophisticated definition where language refers to all its nuanced components, including but not limited to grammar, prosody, facial expression, and gesture. Due to its complexity and sensitivity, many aspects of language can be indicative of a person’s mental health. For example, increasing levels of depression have been shown to be correlated with increased pause lengths in speech and decreased speaking rates. There also exists evidence that psychopaths have difficulty interpreting and expressing emotion in language and therefore use fewer and less intense emotion words, more disfluencies, and distancing language (more past tense and articles). Language is pervasive and a substantial body of research has shown that language can be useful in characterizing mental health, including mood disorders (depression, bipolar), personality disorders (narcissism, psychopathy), psychotic disorders (schizophrenia, substance abuse), and post-traumatic stress disorder.
However, it is hard to believe that a human can simultaneously pick up and continuously monitor linguistic characteristics such a speech pause rates, speaking rate, emotional word use, and tense. Here I believe computers are key. Computers can process massive amounts of data quickly and efficiently, which is exactly why we can and should use them as a tool for diagnosing and monitoring mental health. A collaborative effort between humans and computers has the potential to have a tremendously positive impact on the world of mental health and for that reason my goal as a researcher is to build technologies for mental health applications. For my dissertation project, I am collaborating with USC Institute of Creative Technologies and Dr. Stefan Scherer to build a multimodal computer system that uses data (video/audio/text) to assess an individual’s level of depression. The data I am using is part of the DCAPS (Detection and Computational Analysis of Psychological Signals) project. The data consists of interviews between individuals and a virtual human who conducts the interview. The ultimate goal of my project is to develop a tool that can help clinicians interview, monitor, and diagnose individuals with depression.
So, how do I fit into the FI? FI’s mission is to advance greater equity and innovation in higher education. Technology is an integral part in the advance. In order for technology to help all people, it must be freely and equally available and accessible to everyone. As a FI’s fellow, I hope to promote, create, and share open-source tools and resources. In addition, as a female who conducts research in a STEM field, I understand the struggles and challenges that underrepresented individuals face and I believe changes need to be made. It’s forecasted that by the year 2020, there will be 1.4 million jobs available in computing related fields. US graduates are on track to fill 29% of those jobs, while women are on track to fill just 3%. The gender gap in computing is a major issue and as a FI’s fellow I hope to help combat this issue. In order to do so, I’ll serve many roles, including web developer, research analyst, event planner, and blogger. I invite you to follow my journey as a Futures Initiative fellow and PhD candidate.