"Rate My Therapist": Automated Detection of Empathy in Drug and Alcohol Counseling via Speech and Language Processing

PLoS ONE

Volumn 10, Issue 12, 2015, Pages

  Bo Xiao, ^a   Imel, Zac E ^b   Georgiou, Panayiotis G ^a   Atkins, David C ^c   Narayanan, Shrikanth S ^a  

^a University of Southern California ^*  (United States)

^b UNIVERSITY OF UTAH   (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALCOHOL;

ACCURACY; ARTICLE; AUTOMATIC SPEECH RECOGNITION; AUTOMATION; BEHAVIOR ASSESSMENT; CONTROLLED STUDY; DATA ANALYSIS; EMPATHY; FEMALE; HUMAN; MALE; MENTAL PERFORMANCE; MOTIVATIONAL INTERVIEWING; NATURAL LANGUAGE PROCESSING; OUTCOME ASSESSMENT; PATIENT ASSESSMENT; PATIENT COUNSELING; PREDICTION; PROCESS DEVELOPMENT; PSYCHOTHERAPY; SCORING SYSTEM; SPEECH THERAPY; TASK PERFORMANCE; ALCOHOLISM; COUNSELING; LANGUAGE; MIDDLE AGED; PROFESSIONAL-PATIENT RELATIONSHIP; SPEECH;

ALCOHOLISM; AUTOMATION; COUNSELING; EMPATHY; FEMALE; HUMANS; LANGUAGE; MALE; MIDDLE AGED; MOTIVATIONAL INTERVIEWING; PROFESSIONAL-PATIENT RELATIONS; PSYCHOTHERAPY; SPEECH;

EID: 84955508891     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0143055     Document Type: Article

References (56)

1. SAMHSA. The Treatment Episode Data Set (TEDS) 2000-2010. State Admissions to Substance Abuse Treatment Services. DASIS Series: S-63, HHS Publication No. SMA-12-4729. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2012.
2. Miller WR, Rollnick S. Motivational Interviewing. 3rd ed. New York: Guilford; 2012.
3. Baldwin SA, Imel ZE. Therapist effects. In: Lambert M. ed. Bergin and Garfield's Handbook of Psychotherapy and Behavior Change 5th ed. New Jersey: Wiley; 2013:258-297.
4. Kirschenbaum H. Carl Rogers's life and work: An assessment on the 100th anniversary of his birth. J of Couns Dev. 2004; 82:116-124.
5. Høglend P. Exploration of the patient-therapist relationship in psychotherapy. Am J Psychiatry. 2014: 171:1056-1066.
6. Holmes EA, Craske MG, Graybiel AM. Psychological treatments: A call for mental-health science. Nature News. 2014; 511:287-289.
7. DeRubeis RJ, Siegle GJ, Hollon SD. Cognitive therapy versus medication for depression: treatment outcomes and neural mechanisms. Nat Rev Neurosci. 2008; 9:788-796.
8. Campbell ANC, Nunes EV, Matthews AG, Stitzer M, Miele GM, Polsky D, et al. Internet-Delivered Treatment for Substance Abuse: A Multisite Randomized Controlled Trial. Am J Psychiatry. 2014; 171:683-690.
9. Miller WR, Rose GS. Toward a theory of motivational interviewing. Am Psychol. 2009; 64:527-537.
10. Schwalbe CS, Oh HY, Zweben A. Sustaining motivational interviewing: a meta-analysis of training studies. Addiction. 2014; 109:1287-1294.
11. Moyers TB, Martin T, Manuel JK, Hendrickson SM, Miller WR. Assessing competence in the use of motivational interviewing. J Subst Abuse Treat. 2005; 28:19-26.
12. Carroll KM. Lost in translation? Moving contingency management and cognitive behavioral therapy into clinical practice. Ann N Y Acad Sci. 2014; 1327:94-111.
13. Narayanan S, Georgiou PG. Behavioral signal processing: Deriving human behavioral informatics from speech and language. Proc IEEE Inst Electron Eng. 2013; 101:1203-1233.
14. Atkins DC, Steyvers M, Imel ZE, Smyth P. Scaling up the evaluation of psychotherapy: evaluating motivational interviewing fidelity via statistical text classification. Implement Sci. 2014; 9:49-49.
15. Imel ZE, Steyvers M, Atkins DC. Computational psychotherapy research: scaling up the evaluation of patient-provider interactions. Psychotherapy. 2015; 52(1):19-30.
16. Georgiou PG, Black MP, Lammert A, Baucom BR, Narayanan SS. 'That's aggravating, very aggravating': Is it possible to classify behaviors in couple interactions using automatically derived lexical features? Proc ACII. 2011; 6974:87-96.
17. Shin J, Georgiou PG, Narayanan SS. Towards effective design of multimodal interface for speech-tospeech translation system: Analysis of longitudinal user behaviors over time and user strategies coping with errors. Computer Speech & Language. 2013; 27:554-571.
18. Anguera MX, Bozonnet S, Evans N, Fredouille C, Friedland G, Vinyals O. Speaker Diarization: A Review of Recent Research. IEEE Trans Audio Speech Lang Process. 2012; 20:356-370.
19. Heigold G, Ney H, Schluter R, Wiesler S. Discriminative training for automatic speech recognition: Modeling, criteria, optimization, implementation, and performance. IEEE Signal Process Mag. 2012; 29:58-69.
20. Kenny P, Reynolds D, Castaldo F. Diarization of telephone conversations using factor analysis. IEEE J Sel Top Signal Process. 2010; 4:1059-1070.
21. Hinton G, Deng L, Yu D, Dahl G, Mohamed A, Jaitly N, et al. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Process Mag. 2012; 29:82-97.
22. Tranter SE, Reynolds DA. An overview of automatic speaker diarization systems. IEEE Trans Audio Speech Lang Process. 2006; 14:1557-1565.
23. Baer J, Wells E, Rosengren D. Agency context and tailored training in technology transfer: A pilot evaluation of motivational interviewing training for community counselors. J Subst Abuse Treat. 2009; 37:191-202.
24. Lord SP, Can D, Yi M, Marin R, Dunn CW, Imel ZE, et al. Advancing methods for reliably assessing motivational interviewing fidelity using the Motivational Interviewing Skills Code. J Subst Abuse Treat. 2015; 49:50-57.
25. Moyers TB, Martin T, Manuel J. Motivational Interviewing Treatment Integrity (MITI) Coding System. The University of New Mexico Center on Alcoholism. 2005. Available: http://casaa-0031.unm/edu.
26. Ghosh PK, Tsiartas A, Narayanan S. Robust Voice Activity Detection Using Long-Term Signal Variability. IEEE Transactions on Audio, Speech, and Language Processing. 2010; 19(3):600-613.
27. Zhang X-L, Wu J. Deep Belief Networks Based Voice Activity Detection. IEEE Transactions on Audio, Speech, and Language Processing. 2013; 21(4):697-710.
28. Van Segbroeck M, Tsiartas A, Narayanan S. A robust frontend for VAD: exploiting contextual, discriminative and spectral cues of human voice. Proc InterSpeech. 2013;704-708.
29. Wang W, Lu P, Yan Y. An improved hierarchical speaker clustering, ACTA ACUSTICA. 2008; 33:9.
30. Huang CW, Xiao B, Georgiou PG. Unsupervised Speaker Diarization Using Riemannian Manifold Clustering. Proc InterSpeech; 2014;567-571.
31. Levinson SE, Rabiner LR, Sondhi MM. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition. The Bell System Technical Journal. 1983; 62(4):1035-1074.
32. Brown PF, deSouza PV, Mercer RL, Pietra VJD, Lai JC. Class-based n -gram models of natural language. Computational Linguistics. 1992; 18(4):467-479.
33. Stolcke A. SRILM-an extensible language modeling toolkit. Proc InterSpeech. 2002.
34. Povey D, Ghoshal A, Boulianne G, Burget L, Glembek O, Goel N, et al. The Kaldi speech recognition toolkit. Proc ASRU; 2011.
35. Can D, Gibson J, Vaz C, Georgiou PG, Narayanan SS. Barista: A framework for concurrent speech processing by usc-sail. ICASSP 2014-2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2014:3306-3310.
36. Chang C-C, Lin C-J. LIBSVM: A library for support vector machines. Transactions on Intelligent Systems and Technology (TIST. 2011; 2(3):1-27.
37. Kuhn M, Johnson K. Applied Predictive Modeling. New York: Springer; 2013.
38. Atkins DC, Rubin T, Steyvers M, Doeden MA, Baucom BR, Christensen A. Topic models: A novel method for modeling couple and family text data. J Fam Psychol. 2012; 26:816-827.
39. van den Broek EL, van der Sluis F, Dijkstra T. Therapy progress indicator (TPI): Combining speech parameters and the subjective unit of distress. Proc ACII;2009:1-6.
40. Cohn JF, Kruez TS, Matthews I, et al. Detecting depression from facial actions and vocal prosody. Proc ACII 2009;1-7.
41. Xiao B, Imel ZE, Atkins DC, Georgiou P, Narayanan S. Analyzing Speech Rate Entrainment and Its Relation to Therapist Empathy in Drug Addiction Counseling, Proc Interspeech; 2015:2489-2493, Dresden, Germany.
42. Imel ZE, Barco JS, Brown H, Baucom BR, Baer JS, Kircher J, Atkins DC. Synchrony in vocally encoded arousal as an indicator of therapist empathy in motivational interviewing. J Couns Psychol, 2014; 61:146-53.
43. Kahneman D, Klein G. Conditions for intuitive expertise: a failure to disagree. Am Psychol. 2009; 64:515-526.
44. Miller WR, Sorensen JL, Selzer JA. Disseminating evidence-based practices in substance abuse treatment: a review with suggestions. J Subst Abuse Treat. 2006; 31:25-39.
45. Tracey TJG, Wampold BE, Lichtenberg JW, Goodyear RK. Expertise in Psychotherapy: An Elusive Goal? Am Psychol. 2014; 69:218-219.
46. Ladany N, Hill C, Corbett M. Nature, extent, and importance of what psychotherapy trainees do not disclose to their supervisors. J Couns Psychol. 1996; 43:10-24.
47. Santa Ana EJ, Martino S, Ball SA, Nich C, Frankforter TL, Carroll KM. What is usual about "treatmentas- usual?" Data from two multisite effectiveness trials. J Subst Abuse Treat. 2008; 35:369-379.
48. Magill M, Gaume J, Apodaca TR, Walthers J, Mastroleo NR, Borsari B, et al. The Technical Hypothesis of Motivational Interviewing: A Meta-Analysis of MI's Key Causal Model. J Consult Clin Psychol. 2014; 82(6):973-983.
49. Leichsenring F, Salzer S, Beutel ME, Herpertz S, Hiller W, Hoyer J, et al. Psychodynamic therapy and cognitive-behavioral therapy in social anxiety disorder: a multicenter randomized controlled trial. Am J Psychiatry. 2013; 170:759-67.
50. Xiao B, Bone D, Segbroeck MV, Imel ZE, Atkins, DC, Panayiotis GG, et al. Modeling therapist empathy through prosody in drug addiction counseling. Proc Interspeech; 2014:213-217.
51. Cohn DA, Ghahramani Z, Jordan MI. Active Learning with Statistical Models. Journal of Artificial Intelligence Research, 1996; 4:129-145.
52. Tollison S, Lee C, Neighbors C, Neil T. Questions and reflections: the use of motivational interviewing microskills in a peer-led brief alcohol intervention for college students. Behav Ther. 2008; 39:183-194.
53. Lee CM, Neighbors C, Lewis MA, Kaysen D, Mittmann A, Geisner IM, et al. Randomized controlled trial of a Spring Break intervention to reduce high-risk drinking. J Consult Clin Psychol. 2014; 82:189-201.
54. Neighbors C, Lee CM, Atkins DC, Lewis MA, Kaysen D, Mittmann A, et al. A randomized controlled trial of event-specific prevention strategies for reducing problematic drinking associated with 21st birthday celebrations. J Consult Clin Psychol. 2012:850-862.
55. Krupski A, Joesch JM, Dunn C, Donovan D, Bumgardner K, Lord SP, et al. Testing the effects of brief intervention in primary care for problem drug use in a randomized controlled trial: Rationale, design, and methods. Addict Sci Clin Pract. 2012; 7:27.
56. Lee CM, Kilmer JR, Neighbors C, Atkins DC, Zheng C, Walker DD, et al. Indicated prevention for college student marijuana use: A randomized controlled trial. J Consult Clin Psychol. 2013; 81:702-709.