Sentiment Analysis for PTSD Signals
This was for the pathology challenge.
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- PTSD Post Traumatic Stress Disorder;
The team was led by Ph. Speech and Audio Processing, Watson Research Center in Hawthorne, NY to recognize outstanding student researchers in the field of multimedia. She was joined by 9 other students from leading research groups in institutions around the country.
The specific application focus is on cross language interactions in health care settings. USC computer scientists, communication specialists and health professionals hope to create a cheap, robust and effective speech-to-speech translation system for clinics, emergency rooms and ambulances. Read more in USC news A million-dollar grant awarded to a team of USC researchers could make communication with doctors across language barriers a lot easier, thanks to a new advanced translation system.
Matt Black was awarded the Simon Ramo Fellowship for Angeliki Metallinou was awarded the Myronis Endowed Fellowship for Viterbi Professor in the Ming Hsieh Department of Electrical Engineering, who has joint appointments in linguistics, psychology and computer science.
Demetrios Sapounas (Author of Sentiment Analysis for Ptsd Signals)
Ozlem Kalinli is spending the summer of interning at Microsoft Research. Emily Mower was awarded the Intel Fellowship. Analyzing the multimodal behaviors of users of a speech-to-speech translation device by using concept matching scores. Watson Research Center, doing research under Gerasimos Potamianos on acoustic event detection.
Sentiment Analysis For Ptsd Signals Springerbriefs In Computer Science
They are working with the CHIL corpus, consisting of multiple channels of far-field audio recordings from multi-person meeting scenarios. Their goal is to detect specific non-speech acoustic events door knocks, paper noises, applause, etc. Graduate School Fellowships in Digital Scholarship are designed to foster innovative multimedia research that expands the potential of academic publication via emergent and transitional media. Alexa then guides him through a follow-up questionnaire stop by our table to see this in action!
While Devin is reporting his incident, our servers are running an analysis in the background, leveraging the Eyeris emotion recognition web API. We combine these signals with textual data signals using the Watson API in order to build a model of stress or anxiety. We tested this model on a corpus of YouTube videos containing police report footage such as this one.
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By using computer vision to generate new signals and algorithms, we can both provide insights into the mental health of a first responder, and follow up in real time with Alexa use the appropriate verbal queues. When Devin is finished with the main part of his report, Alexa guides him through follow-ups, taking into account the sentiment analysis performed in the video.
He completes his report. But how is this data surfaced?
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An administrative dashboard allows appropriate supervisors and analysts to view the data relating to mental health and emotional stability of their officers. To help us further visualize this data and for the sake of a cool demo , we can also see this data in real-time as the officer completes his report. We expect to be able to sell this product as a platform to police departments, such as LVPD, and municipalities where it will enhance the safety and security of their officers and the citizens they serve.
We can talk all day about the features we can layer on top of this—getting data from body cameras, improvements to the stress algorithm using heart rate detection, smarter incident report auto-generation.
But what made us most excited about this concept was a conversation with two officers who were on duty nearby this morning. They spoke passionately about how law enforcement is rapidly changing and becoming more aware of these issues. Log in Sign up. Advanced Work in progress 2 days 1, Things used in this project. Admin panel.