Assessing the Validity of Voice Stress Analysis Tools in a Jail Setting

Damphousse, Kelly R.; Pointon, Laura; Upchurch, Deidra; Moore, Rebecca

doi:10.1037/e664702007-001

Cited by 20 publications

(28 citation statements)

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“…There was no instance in which the LVA produced correct decisions beyond chance. These results are remarkably similar to those reported in the field-based study by Damphousse et al (7). In that study, involving police arrestees who lied about drug usage, correct detection of deceptive persons averaged only 15%.…”

Section: Discussionsupporting

confidence: 90%

“…In this study, the voice devices failed to identify correctly the arrestees' deception. Only about 15% of the arrestees who recently used drugs but reported that they had not were identified as being deceptive (5,7). This result complements previous research findings, showing that the voice analyzers are as ineffective in a real world setting as they are in laboratory-based studies.…”

supporting

confidence: 83%

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The Accuracy of Auditors' and Layered Voice Analysis (LVA) Operators' Judgments of Truth and Deception During Police Questioning*

Horváth

McCloughan

Weatherman

et al. 2013

Journal of Forensic Sciences

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The purpose of this study was to determine if auditors could identify truthful and deceptive persons in a sample (n = 74) of audio recordings used to assess the effectiveness of layered voice analysis (LVA). The LVA employs an automated algorithm to detect deception, but it was not effective here. There were 31 truthful and 43 deceptive persons in the sample and two LVA operators averaged 48% correct decisions on truth-tellers and 25% on deceivers. Subsequent to the LVA analysis the recordings were audited by three interviewers, each independently rendering a decision of truthful or deceptive and indicating their confidence. Auditors' judgments averaged 68% correct decisions on truth-tellers and 71% on deceivers. Auditors' detection rates, generally, exceeded chance and there was significantly (p < 0.05) greater confidence on correct than incorrect judgments of deceivers but not on truth-tellers. These results suggest that the success reported for LVA analysis may be due to operator's judgment.

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Section: Discussionsupporting

confidence: 90%

supporting

confidence: 83%

The Accuracy of Auditors' and Layered Voice Analysis (LVA) Operators' Judgments of Truth and Deception During Police Questioning*

Horváth

McCloughan

Weatherman

et al. 2013

Journal of Forensic Sciences

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“…Other research (Damphousse et al 2007), plus our field studies (Hollien/Harnsberger 2006), confirmed these findings. In short, it is clear that the CVSA and the LVA devices were not able to detect deception or stress; indeed, both operated only at chance levels.…”

Section: Deceptionsupporting

confidence: 77%

About forensic phonetics

Hollien

2012

linguistica

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ABOUT FORENSIC PHONETICSThis article sets forth the goals and content of Forensic Phonetics and its major elements. Considered are 1) the processing and analysis of spoken utterances, 2) enhancement of speech intelligibility (re: surveillance and other recordings), 3) authentication of recordings, 4) speaker identification, and 5) detection of deception, intoxication, and emotions in speech. Stress in speech, and the psychological stress evaluation systems that some individuals attempt to use as lie detectors also will be considered.

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“…6 One notably promising aspect in social media is that most verbal cues are based on text. Verbal deception detection has been used to identify identity deception (such as through similarity analysis of profile information (80.4%-98.6% accuracy); 30 similarity analysis with natural language processing to identify identity deception through writing patterns (68.8% accuracy); 25 cross-referencing information between a social network and anonymized social networks containing the nodes in the first network to evaluate the trustworthiness of social network profile attributes (40%-80% recall, depending on metric and technique when baseline recall is 20%); 5 and natural language processing to identify text features that betray deceptive email messages (75.4% accuracy).…”

Section: Challengesmentioning

confidence: 99%

Online deception in social media

2014

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A S E D technologies has revolutionized the way content is generated and exchanged through the Internet, leading to proliferation of social-media applications and services. Social media enable creation and exchange of user-generated content and design of a range of Internet-based applications. This growth is fueled not only by more services but also by the rate of their adoption by users. From 2005 to 2013, users and developers alike saw a 64% increase in the number of people using social media; 1 for instance, Twitter use increased 10% from 2010 to 2013, and 1.2 billion users connected in 2013 through Facebook and Twitter accounts. 24 However, the ease of getting an account also makes it easy for individuals to deceive one another. Previous work on deception found that people in general lie routinely, and several efforts have sought to detect and understand deception. 20 Deception has been used in various contexts throughout human history (such as in World War II and the Trojan War) to In social media, deception can involve content, sender, and communication channel or all three together.The nature of a social medium can influence the likelihood of deception and its success for each deception technique.Deception detection and prevention are complicated by lack of standard online deception detection, of a computationally efficient method for detecting deception in large online communities, and of social media developers looking to prevent deception.

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Assessing the Validity of Voice Stress Analysis Tools in a Jail Setting

Cited by 20 publications

References 0 publications

The Accuracy of Auditors' and Layered Voice Analysis (LVA) Operators' Judgments of Truth and Deception During Police Questioning*

The Accuracy of Auditors' and Layered Voice Analysis (LVA) Operators' Judgments of Truth and Deception During Police Questioning*

About forensic phonetics

Online deception in social media

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