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Selected Recent Publications
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Bayesian Unsupervised Topic Segmentation. Eisenstein and Barzilay. EMNLP 2008.
- A new method to segment text and speech transcripts into topically-coherent units, using both lexical cohesion and cue phrases. First paper to show that cue phrases can be used without supervision. combining them with cohesion in a generative Bayesian framework.
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- Gestural Cohesion for Topic Segmentation. Eisenstein, Barzilay, and Davis. ACL 2008.
- Coherent discourse topics contain internally consistent gestural forms, paralleling
similar work on the distribution of lexical items. Automatically extracted gesture
features are used to improve unsupervised topic segmentation on dialogues.
Unsupervised Multilingual Learning for POS Tagging. Snyder, Naseem, Eisenstein and Barzilay. EMNLP 2008.
- Unsupervised part-of-speech tagging works better when applied to multiple languages simultaneously.
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Modeling Gesture
Salience as a Hidden Variable for Coreference Resolution and Keyframe
Extraction. Eisenstein, Barzilay, and Davis.
Journal of Artificial Intelligence Research, volume 31, 353-398.
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Describes the use of a conditional hidden variable model for gesture salience
in coreference resolution. The model improves performance on coreference
resolution, and the estimates of gesture salience can be transferred
directly to select keyframes containing interesting gestures.
Discourse Topic and Gestural Form. Eisenstein, Barzilay, and Davis. AAAI 2008.
- A quantitative analysis of the influence of speaker and topic on gestural form. Using low-level
interest point features, it is possible to show that multiple speakers use similar gestures when describing
the same topic.
Election Prediction
A side interest of mine is statistical models for predicting election results based on polls. I did pretty well predicting the US Senate elections in 2006.
Contact
Beckman Institute for Advanced Science and Technology
University of Illinois Urbana-Champaign
405 N. Mathews St.
Urbana, IL 61801
617-253-2663
jacobe gmail com
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