A Virtual Human Agent for Training Clinical Interviewing Skills to Novice Therapists

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A Virtual Human Agent for Training Clinical Interviewing Skills to Novice Therapists CyberTherapy 2007 Patrick Kenny (kenny@ict.usc.edu) Albert Skip Rizzo, Thomas Parsons, Jonathan Gratch, William Swartout 1 Virtual Humans Group at ICT Researching Artificial Intelligence in fields related to building Artificial Humans Cognitive and Emotion Modeling Natural Language Understanding Mind Speech Recognition Dialog and Discourse Non-Verbal Behavior Body Simulated Worlds / Integrated Systems World 2 1

Virtual Humans to Virtual Patients Re-use our Virtual Human technology and apply it to the medical field Built an interactive Virtual Patient The intention is to use it to train: Clinicians Interaction Interviewing skills Diagnosis skills Virtual patients are virtual interactive agents who are design to simulate a particular clinical presentation of a patient with a high degree of consistency and realism Unfunded Project put together Over 3-4 months 3 Justin The Virtual Patient Teenage Boy with Conduct Disorder Trainee acts as a clinician that needs to perform an Initial Intake Interview - history and diagnosis Idea is to train interpersonal skills such as: Leadership Cultural Awareness Negotiation Interviewing Communications 4 2

VHumans need to be Responsive Able to interact and talk in a timely and natural manner (Verbal and Non-verbal) Behavior not pre-scripted Interpretable, Able to understand them and they you Believable Act and look like real people (Cartoons characters are ok also Realism <> Believability) Virtual humans: Need to act the role they are assigned 5 Virtual Humans at ICT TacQ Question / Answer s C3IT Tactical Questioning In Immersive Environments 6 3

TacQ Emotional Dialog Modeling ELECT Bi-Lateral Negotiations Rapport Evaluation of Nonverbal Behavior Influence 7 Doctors without Borders Cognition and Emotion Models SASO-ST Bi-Lateral Negotiations SASO-EN Multi-Lateral Negotiations In the SASO system, a trainee interacts with a virtual human representing a doctor without borders doctor to negotiate the move of the clinic, as it is in the middle of a strategic operational area. 8 4

SASO-EN Show Video "The difference between fiction and reality? Fiction has to make sense. --Tom Clancy 9 Modeling Rational Behavior Virtual Humans Modeling Irrational Behavior Virtual Patients 10 5

DSM-IV: Conduct Disorder Domain A patient that has a conduct disorder is characterized by (3 or more of): Aggression to People and Animals Destruction of property Deceitfulness or theft Serious violations of rules Chose someone with this problem, because if he didn t respond properly then it would be attributed to the disorder and not technology related 11 Building a Virtual Human Create the History and background Artwork Environment 12 6

Building a Virtual Human Create the Get the Dialog Roleplaying DSM-IV Wizard of Oz Tests Roleplaying in the Domain Role play between people One plays the Clinician Other plays the Patient with conduct disorder Skip Rizzo naturally fit this role, so he played this part Structured and un-structured 13 Building a Virtual Human Create the Get the Dialog Capture the Behavior Roleplaying Videos What makes sense The goal is to capture the dialog interchange, the verbal and non-verbal behavior 14 7

Building a Virtual Human Create the Get the Dialog Capture the Behavior Dialog is also used to build the lexicon for the speech recognizer Questions Responses Build the dialog lexicon 15 Building a Virtual Human Create the Get the Dialog Capture the Behavior Responses can be: On Topic Off-Topic Alternate responses Delayed Repeat Build the dialog lexicon Match the Questions and Answers for the dialog conversation Questions Responses 16 8

Building a Virtual Human Create the Get the Dialog Capture the Behavior Build the dialog lexicon Match the Questions and Answers for the dialog conversation Place the in the environment 17 18 9

Interaction with the Virtual Patient Microphone Speech Recognition Audio Signal Plain Text Question / Response Dialog Management FML Non-Verbal Behavior BML Display Output Virtual Environment (Unreal Tournament) Joint Angles Speech File Control Smart Body Pre-recorded Speech Files Machine: P3 Dual Core, Nvidia 7600 Graphics Card, 2 Meg memory, Dual Monitors, Microphone Speech input 19 Subject Testing of the System Preliminary subject testing Pre-Questionnaire Assess participants clinical skill level Interview with Virtual Patient 30 min Post-Questionnaire (7 point Likert Scale) 35 questions Assess participates knowledge of the VP s condition Assess interaction and believability of character System in general Additionally there was experimenter over-the-shoulder observation of the participants Sample size was 6, but only 3 were of the desired level of clinical competence ( other Vhuman System ~100 ppl) Testing was conducted with the Keck School of Medicine at USC 20 10

Assessment of the System What worked Initial results from the survey suggest the system performed well System simulated real-life experience (ranked 5 or 6) The verbal and non-verbal behavior ranked high, between 5 and 7 Pace of the interview and response time was good What didn t work Some participants found aspects of the system frustrating due to responses not being what they expected and the patient s tendency to repeat some responses too many times Speech model didn t have all the words people spoke, so some lines were interpreted wrong, leading to the wrong response. Patient seemed to be slightly more resistant then anticipated Depth of topics was not adequate, i.e. could only answer a few questions about family matters. 21 Improvements Increase the size of the dialog set for the speech recognizer and dialog manager Include sub-topic area information for each of the conduct disorder areas Have patient track more conversation state and topics More autonomous behavior then just waiting for the next question Create behavior and personality modules Tools to build characters more easily 22 11

Building Research vs Applied Systems It s always a challenge to take research work and apply it in a real setting Things people do that you don t anticipate Need to have iterative design, lots of system testing 23 Future work Seedling Provosts' grant from USC to build a virtual Justina that has been the target of a sexual assault and has to deal with PTSD of the situation Stuff that is hard to train someone on, hard to talk about. Virtual Humans are powerful training tools Just the beginning and new more analysis on how effective it is Cyrsis Game Electronic Arts 2008 24 12

Acknowledgments This work was sponsored by the U.S. Army Research, Development, and Engineering Command (RDECOM), and the content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Mission Rehearsal Exercise Virtual Human Training Prototype 25 13