ACL
2012
11 years 7 months ago
2012
In this paper, we propose a computational approach to generate neologisms consisting of homophonic puns and metaphors based on the category of the service to be named and the prop...
ACL
2012
11 years 7 months ago
2012
The language MIX consists of all strings over the three-letter alphabet {a, b, c} that contain an equal number of occurrences of each letter. We prove Joshi’s (1985) conjecture ...
ACL
2012
11 years 7 months ago
2012
This paper presents the problem within Hittite and Ancient Near Eastern studies of fragmented and damaged cuneiform texts, and proposes to use well-known text classification metr...
ACL
2012
11 years 7 months ago
2012
In this paper, we develop an RST-style textlevel discourse parser, based on the HILDA discourse parser (Hernault et al., 2010b). We significantly improve its tree-building step b...
ACL
2012
11 years 7 months ago
2012
Since we can ‘spin’ words and concepts to suit our affective needs, context is a major determinant of the perceived affect of a word or concept. We view this re-profiling as a...
ACL
2012
11 years 7 months ago
2012
Learning for sentence re-writing is a fundamental task in natural language processing and information retrieval. In this paper, we propose a new class of kernel functions, referre...
ACL
2012
11 years 7 months ago
2012
Previous approaches to instruction interpretation have required either extensive domain adaptation or manually annotated corpora. This paper presents a novel approach to instructi...
ACL
2012
11 years 7 months ago
2012
In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
ACL
2012
11 years 7 months ago
2012
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...
ACL
2012
11 years 7 months ago
2012
We present a holistic data-driven approach to image description generation, exploiting the vast amount of (noisy) parallel image data and associated natural language descriptions ...