Stories can encapsulate complexity, subtlety, and nuance: all of which are implicitly contained in narrative and reasoned about automatically through the mental processes that come naturally to humans. For example, humans can package complicated plots into a relatively small set of well-recognized and meaningful linguistic terms. This summarization ability though has not been available to syste...

This paper analyzes the contribution of semantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety of morphosyntactic features plus semantic roles features is developed and evaluated. Our system achieves an F1 of 81.4% in recognition and a 64.2% in classification. We demonstrate that the application of semantic rol...

HIGH RATES of remarriage in most Western countries (around 40% of all new marriages; Kreider, 2005) have resulted in many adults living in households that include children from a previous relationship. For example, 10% of U.S. fathers and 2% of U.S. mothers live with their partner’s child (Kreider & Fields, 2005). Many couples in stepfamilies are happy in their relationships; others struggle wi...

This paper describes a method of automatic labeling of prosodic information focusing on accent types and accent phrase boundaries for Japanese spoken sentences. They are predicted by CRF (Conditional Random Fields) using linguistic information and F0 contour information. In the prediction of the accent type, we propose a method that uses a provisional accent type predicted by linguistic informa...

A multi-class traffic scene segmentation approach based on scene flow data is presented. Opposed to many other approaches using color or texture features, our approach is purely based on dense depth and 3D motion information. Using prior knowledge on tracked objects in the scene and the pixel-wise uncertainties of the scene flow data, each pixel is assigned to either a particular moving object ...

This paper describes the system that we use for Chinese segmentation task in the 3rd CIPS-SIGHAN bakeoff. We use character sequence labeling method for segmentation, and in order to improve segmentation accuracy over multi-domain, we present a CRF-based Chinese segmentation system integrating supervised, unsupervised and lexical features. We firstly preliminarily segment the target data using C...

We compare the effect of joint modeling of phonological features to independent feature detectors in a Conditional Random Fields framework. Joint modeling of features is achieved by deriving phonological feature posteriors from the posterior probabilities of the phonemes. We find that joint modeling provides superior performance to the independent models on the TIMIT phone recognition task. We ...

In this paper we develop an automatic classifier for a very large set of labels, the WordNet synsets. We employ Conditional Random Fields (CRFs) because of their flexibility to include a wide variety of nonindependent features. Training CRFs on a big number of labels proved a problem because of the large training cost. By taking into account the hypernym/hyponym relation between synsets in Word...

We show that the definition of neighbor in Markov random fields as defined by Besag (1974) when the joint distribution of the sites is not positive is not well-defined. In a random field with finite number of sites we study the conditions under which giving the value at extra sites will change the belief of an agent about one site. Also the conditions under which the information from some sites...

Conditional Random Fields are among the most popular techniques for image labelling because of their flexibility in modelling dependencies between the labels and the image features. This paper addresses the problem of efficient classification of partially occluded objects. For this purpose we propose a novel Gaussian Mixture Model based on a sequential training procedure, in combination with mu...