2005 Presentations (Communicative Events)
Distinguishing Deceptive from Non-Deceptive Speech
To date, studies of deceptive speech have largely been confined to descriptive studies and observations from subjects, researchers, or practitioners, with few empirical studies of the specific lexical or acoustic/prosodic features which may characterize deceptive speech. We present results from a study seeking to distinguish deceptive from non-deceptive speech using machine learning techniques on features extracted from a large corpus of deceptive and non-deceptive speech. This corpus employs an interview paradigm that includes subject reports of truth vs. lie at multiple temporal scales. We present current results comparing the performance of acoustic/prosodic, lexical, and speaker-dependent features and discuss future research directions.
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Files
- hirschberg_al_05.pdf application/pdf 114 KB Download File
More About This Work
- Academic Units
- Computer Science
- Publisher
- Proceedings of Eurospeech'05
- Published Here
- June 1, 2013