Analyzing Speech to Detect Financial Misreporting

@article{Hobson2011AnalyzingST,
  title={Analyzing Speech to Detect Financial Misreporting},
  author={Jessen L. Hobson and William J. Mayew and Mohan Venkatachalam},
  journal={Cognitive Linguistics: Cognition},
  year={2011}
}
We examine whether vocal markers of cognitive dissonance are useful for detecting financial misreporting. We use speech samples of CEOs during earnings conference calls, and generate vocal dissonance markers using automated vocal emotion analysis software. We begin by assessing construct validity for the software‐generated dissonance markers by correlating them with four dissonance‐from‐misreporting proxies obtained in a laboratory setting. We find a positive association between these proxies… 

Discussion of Analyzing Speech to Detect Financial Misreporting

One of the most important tasks facing investors, auditors, and regulators is to identify misreporting by managers, preferably using ex ante signals. Hobson, Mayew, and Venkatachalam [2012]

Discussion of Analyzing Speech to Detect Financial Misreporting

One of the most important tasks facing investors, auditors, and regulators is to identify misreporting by managers, preferably using ex ante signals. Hobson, Mayew, and Venkatachalam [2012]

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