Nilsson and Nivre (2009) introduced a treebased model of persons’ eye movements in reading. The individual variation between readers reportedly made application across readers impossible. While a tree-based model seems plausible for eye movements, we show that competitive results can be obtained with a linear CRF model. Increasing the inductive bias also makes learning across readers possible. ...

This paper describes the winning entry to the ALTA Shared Task 2013. The theme of the shared task was recovery of casing and punctuation information from degraded English text. We tackle the task as a sequential labeling problem, jointly learning the casing and punctuation labels. We implement our sequential classifier using conditional random fields, trained using linguistic features extracted...

This paper presents models for detecting agreement/disagreement between speakers in English and Arabic broadcast conversation shows. We explore a variety of features, including lexical, structural, durational, and prosodic features. We experiment with these features using Conditional Random Fields models and conduct systematic investigations on efficacy of various feature groups across language...

Automatically segmenting organs in monocular laparoscopic images is an important and challenging research objective in computerassisted intervention. For the uterus this is difficult because of high interpatient variability in tissue appearance and low-contrast boundaries with the surrounding peritoneum. We present a framework to segment the uterus which is completely automatic, requires only a...

We present a simple and effective approach to the task of grapheme-tophoneme conversion based on a set of manually edited grapheme-phoneme mappings which drives not only the alignment of words and corresponding pronunciations, but also the segmentation of words during model training and application, respectively. The actual conversion is performed with the help of a conditional random field mod...

We propose a novel approach for developing a two-stage document-level discourse parser. Our parser builds a discourse tree by applying an optimal parsing algorithm to probabilities inferred from two Conditional Random Fields: one for intrasentential parsing and the other for multisentential parsing. We present two approaches to combine these two stages of discourse parsing effectively. A set of...

In this paper, we present state-of-the art concept tagging results on a new corpus for Polish SLU. For this language, it is the first large-scale corpus (~200 different concepts) which has been semantically annotated and will be made publicly available. Conditional Random Fields have proven to lead to best results for string-to-string translation problems. Using this approach, we achieve a conc...

Surface realisers in spoken dialogue systems need to be more responsive than conventional surface realisers. They need to be sensitive to the utterance context as well as robust to partial or changing generator inputs. We formulate surface realisation as a sequence labelling task and combine the use of conditional random fields (CRFs) with semantic trees. Due to their extended notion of context...

This paper describes experiments in classifying sentences of medical abstracts into a number of semantic classes given by section headings in structured abstracts. Using conditional random fields, we obtain F -scores ranging from 0.72 to 0.97. By using a small set of sentences that appear under the PARTICPANTS heading, we demonstrate that it is possible to recognize sentences that describe popu...