| Paper: | SLP-P17.2 | ||
| Session: | Spoken Language Modeling, Identification and Characterization | ||
| Time: | Thursday, May 18, 16:30 - 18:30 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Paralinguistic and Nonlinguistic Information | ||
| Title: | Combining Prosodic Lexical and Cepstral Systems for Deceptive Speech Detection | ||
| Authors: | Martin Graciarena, SRI International, United States; Elizabeth Shriberg, Andreas Stolcke, SRI International / University of California, Berkeley, United States; Frank Enos, Julia Hirschberg, Columbia University, United States; Sachin Kajarekar, SRI International, United States | ||
| Abstract: | We report on machine learning experiments to distinguish deceptive from nondeceptive speech in the Columbia-SRI-Colorado (CSC) corpus. Specifically, we propose a system combination approach using different models and features for deception detection. Scores from an SVM system based on prosodic/lexical features are combined with scores from a Gaussian mixture model system based on acoustic features, resulting in improved accuracy over the individual systems. Finally, we compare results from the prosodic-only SVM system using features derived either from recognized words or from human transcriptions. | ||
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