Anna Kazantseva

• Research Officer at National Research Council Canada

As the quality of contemporary speech synthesis improves, so too does the interest from language communities in developing text-to-speech (TTS) systems for a variety of real-world applications. Much of the work on TTS has focused on high-resource languages, resulting in implicitly resource-intensive paths to building such systems. The goal of this...

We describe the statistical machine translation system developed at the National Research Council of Canada (NRC) for the Russian-English news translation task of the First Conference on Machine Translation (WMT 2016). Our submission is a phrase-based SMT system that tackles the morphological complexity of Russian through comprehensive use of lemma...

In a large-scale study of how people find topical shifts in written text, 27 annotators were asked to mark topically continuous segments in 20 chapters of a novel. We analyze the resulting corpus for inter-annotator agreement and examine disagreement patterns. The results suggest that, while the overall agreement is relatively low, the annotators s...

News is not simply a straight re-telling of events, but rather an interpretation of those events by a reporter, whose feelings and opinions can often become part of the story itself. Research on automatic summarization of news articles has thus far focused on facts rather than emotions, but perhaps emotions can be significant in news stories too. T...

This paper presents a new algorithm for linear text segmentation. It is an adaptation of Affinity Propagation, a state-of-the-art clustering algorithm in the framework of factor graphs. Affinity Propagation for Segmentation, or APS, receives a set of pairwise similarities between data points and produces segment boundaries and segment centres -- da...

We present an approach to the automatic creation of extractive summaries of literary short stories. The summaries are produced with a specific objective in mind: to help a reader decide whether she would be interested in reading the complete story. To this end, the summaries give the user relevant information about the setting of the story without...

This paper presents experiments with the evaluation of automatically produced summaries of literary short stories. The summaries are tailored to a particular purpose of helping a reader decide whether she wants to read the story. The evaluation procedure includes extrinsic and intrinsic measures, as well as subjective and factual judgments about th...

This paper describes a system that pro- duces extractive summaries of short works of literary fiction. The ultimate purpose of produced summaries is de- fined as helping a reader to determine whether she would be interested in read- ing a particular story. To this end, the summary aims to provide a reader with an idea about the settings of a story...

Work at the University of Ottawa on text summarization in connection with the Document Understanding Conference 2006 advanced along two tracks. We continued to refine and expand the corpus of SCU-marked documents which we created last year from materials that conference participants received from the group at Columbia University. We also developed...

News is not simply a straight re-telling of events, but rather an interpretation of those events by a reporter, where the feelings and opinions of that reporter can often become part of the story itself. Research on automatic sum-marization of news articles has historically fo-cused on facts and not emotions, but perhaps emotions can be significant...