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Unmasking Identity: Speaker Profiling for Forensic Linguistic Purposes

Published online by Cambridge University Press:  13 March 2015

Natalie Schilling
Affiliation:
Georgetown Universityns3@georgetown.edu
Alexandria Marsters
Affiliation:
Georgetown Universityam2267@georgetown.edu

Abstract

When an anonymous speech sample is associated with a criminal matter, for example in the case of a phoned-in bomb threat or ransom demand, forensic linguistic profiling may be used to infer attributes of the speaker from his or her linguistic characteristics. In this review, we present research and case examples outlining what types of speaker characteristics are discoverable via speaker profiling by expert linguists, for example, gender, age, and region of socialization. We also consider different methods in speaker profiling, including aural-perceptual, acoustic phonetic, and automated, and briefly discuss expert versus nonexpert speaker profiling, as well as the proper role of linguistic profilers versus law enforcement and legal professionals, government agencies, and others with whom forensic linguists work. Finally, we address the problem of voice and dialect disguise, including what types of disguises criminals may effect and what methods can be used to unmask them, including human and automated. We illustrate our points by alluding, throughout the review, to various elements of a case in which we recently served as expert linguistic profilers.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2015 

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References

ANNOTATED BIBLIOGRAPHY

Eriksson, Anders. (2010). The disguised voice: Imitating accents or speech styles and impersonating individuals. In Llamas, Carmen & Watt, Dominic (eds.), Language and Identities (pp. 7685). Edinburgh, Scotland: Edinburgh University Press.

The author provided an overview of studies of accent and voice disguise over the past 10+ years, noting that while disguise is not necessarily very common, it can have quite an adverse effect on profiling efforts when employed. In particular, while expert analysts are quite adept at detecting disguise, there currently exist no reliable automatic systems for the detection of disguise. Eriksson advocated for the creation of a database of paired disguised-undisguised speech samples on which to train automated systems. He also called for more research on foreign accent imitation. He discussed the factors that impact people's perceptions of speaker identity, including familiarity with the spoken language/dialect and method/type of disguise (e.g., accent vs. voice).

Jessen, Michael. (2007). Speaker classification in forensic phonetics and acoustics. In Müller, Christian (ed.), Speaker classification I (pp. 180204). Berlin, Germany: Springer.

Based on his own and a review of others’ studies and casework, Jessen discussed voice analysis (i.e., speaker profiling) and voice comparison (i.e., speaker identification). The focus is on which class characteristics seem to be inferable from speech. These include gender, age, so-called “sociolect” (profession, education level), foreign accent, native dialect, and medical conditions. Jessen also noted that it is possible to infer physical characteristics like height from frequency measurements. Jessen pointed to a number of complications in identifying each of the various speaker attributes; the current review further problematizes class characterizations from a sociolinguistic perspective.

Watt, Dominic. (2010). The Identification of the individual through speech. In Llamas, Carmen & Watt, Dominic (eds.), Language and identities (pp. 7685). Edinburgh, Scotland: Edinburgh University Press.

This article presents an overview of speaker identification, which includes profiling unknown speakers for linguistic features indicative of class characteristics, as well as identification of specific individuals. Watt discussed both “lay” or “naïve” speaker identification—day-to-day, impressionistic identification of individuals by listeners untrained in phonetics—and “technical” speaker identification—the examination of a speech sample by a trained speech analysts, using auditory analysis, acoustic phonetic analysis, and automatic speaker recognition technology. The focus is broader than the current review, which focuses more narrowly on expert speaker profiling.

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