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Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Modeling speech disfluency to predict conceptual misalignment in speech survey interfaces

Archived Abstract of Former PSC Researcher

Ehlen, P., M.F. Schober, and Frederick G. Conrad. 2007. "Modeling speech disfluency to predict conceptual misalignment in speech survey interfaces." Discourse Processes, 44(3): 245-265.

Computer-based interviewing systems could use models of respondent disfluency behaviors to predict a need for clarification of terms in survey questions. This study compares simulated speech interfaces that use two such models-a generic model and a stereotyped model that distinguishes between the speech of younger and older speakers-to several non-modeling speech interfaces in a task where respondents provided answers to survey questions from fictional scenarios. The modeling procedure found that the best predictor of conceptual misalignment was a critical Goldilocks range for response latency-hat is, a response time that is neither too slow nor too fast-outside of which responses are more likely to be conceptually misaligned. Different Goldilocks ranges are effective for younger and older speakers.

DOI:10.1080/01638530701600839 (Full Text)

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