Abstract
This chapter focuses on the automatic identification of demographic traits and identity in both speech and writing. We address language use in the virtual world of online games and text entry on mobile devices in the form of chat, email and nicknames, and demonstrate text factors that correlate with demographics, such as age, gender, personality, and interaction style. Also presented here is work on speakers identification in spontaneous language use, where we describe the state of the art in verification, feature extraction, modeling and calibration across multiple environmental conditions. Finally, we bring speech and writing together to explore approaches to user authentication that span language in general. We discuss how speech-specific factors such as intonation, and writing-specific features such as spelling, punctuation, and typing correction correlate and predict one another as a function of users’ sociolinguistic characteristics.
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Acknowledgments
This material is based on work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract D10PC20024. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of DARPA or its contracting agent, the U.S. Department of the Interior, National Business Center, Acquisition & Property Management Division, Southwest Branch. This material is based on work supported by United States Air Force and DARPA under Contract No. FA8750-13-C-0280. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force and DARPA. Approved for Public Release, Distribution Unlimited.
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Lawson, A., Ferrer, L., Wang, W., Murray, J. (2015). Detection of Demographics and Identity in Spontaneous Speech and Writing. In: Baughman, A., Gao, J., Pan, JY., Petrushin, V. (eds) Multimedia Data Mining and Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-14998-1_9
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DOI: https://doi.org/10.1007/978-3-319-14998-1_9
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