Open AccessProceedings Article
Collecting Highly Parallel Data for Paraphrase Evaluation
David L. Chen,William B. Dolan +1 more
- pp 190-200
TLDR
A novel data collection framework is presented that produces highly parallel text data relatively inexpensively and on a large scale that allows for simple n-gram comparisons to measure both the semantic adequacy and lexical dissimilarity of paraphrase candidates.Abstract:
A lack of standard datasets and evaluation metrics has prevented the field of paraphrasing from making the kind of rapid progress enjoyed by the machine translation community over the last 15 years. We address both problems by presenting a novel data collection framework that produces highly parallel text data relatively inexpensively and on a large scale. The highly parallel nature of this data allows us to use simple n-gram comparisons to measure both the semantic adequacy and lexical dissimilarity of paraphrase candidates. In addition to being simple and efficient to compute, experiments show that these metrics correlate highly with human judgments.read more
Citations
More filters
Journal ArticleDOI
From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
TL;DR: This work proposes to use the visual denotations of linguistic expressions to define novel denotational similarity metrics, which are shown to be at least as beneficial as distributional similarities for two tasks that require semantic inference.
Proceedings ArticleDOI
Sequence to Sequence -- Video to Text
Subhashini Venugopalan,Marcus Rohrbach,Jeff Donahue,Raymond J. Mooney,Trevor Darrell,Kate Saenko +5 more
TL;DR: In this article, an end-to-end sequence to sequence model was proposed to generate captions for videos, which can learn the temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model.
Proceedings ArticleDOI
Describing Videos by Exploiting Temporal Structure
TL;DR: In this paper, a spatial temporal 3-D convolutional neural network (3-D CNN) representation of the short temporal dynamics is used for video description, which is trained on video action recognition tasks, so as to produce a representation that is tuned to human motion and behavior.
Proceedings ArticleDOI
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language
TL;DR: A detailed analysis of MSR-VTT in comparison to a complete set of existing datasets, together with a summarization of different state-of-the-art video-to-text approaches, shows that the hybrid Recurrent Neural Networkbased approach, which combines single-frame and motion representations with soft-attention pooling strategy, yields the best generalization capability on this dataset.
Book ChapterDOI
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding
Gunnar A. Sigurdsson,Gül Varol,Xiaolong Wang,Ali Farhadi,Ali Farhadi,Ivan Laptev,Abhinav Gupta,Abhinav Gupta +7 more
TL;DR: This work proposes a novel Hollywood in Homes approach to collect data, collecting a new dataset, Charades, with hundreds of people recording videos in their own homes, acting out casual everyday activities, and evaluates and provides baseline results for several tasks including action recognition and automatic description generation.
References
More filters
Proceedings ArticleDOI
Bleu: a Method for Automatic Evaluation of Machine Translation
TL;DR: This paper proposed a method of automatic machine translation evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run.
Proceedings ArticleDOI
Moses: Open Source Toolkit for Statistical Machine Translation
Philipp Koehn,Hieu Hoang,Alexandra Birch,Chris Callison-Burch,Marcello Federico,Nicola Bertoldi,Brooke Cowan,Wade Shen,C. Corbett Moran,Richard Zens,Chris Dyer,Ondrej Bojar,Alexandra Elena Constantin,Evan Herbst +13 more
TL;DR: An open-source toolkit for statistical machine translation whose novel contributions are support for linguistically motivated factors, confusion network decoding, and efficient data formats for translation models and language models.
Proceedings ArticleDOI
Labeling images with a computer game
Luis von Ahn,Laura Dabbish +1 more
TL;DR: A new interactive system: a game that is fun and can be used to create valuable output that addresses the image-labeling problem and encourages people to do the work by taking advantage of their desire to be entertained.
Proceedings ArticleDOI
Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources
TL;DR: Investigation of unsupervised techniques for acquiring monolingual sentence-level paraphrases from a corpus of temporally and topically clustered news articles collected from thousands of web-based news sources shows that edit distance data is cleaner and more easily-aligned than the heuristic data.
Book
The Pear Stories: Cognitive, Cultural and Linguistic Aspects of Narrative Production
TL;DR: In this paper, the focus is on the verbalization of characters and objects within the discourse, which is the domain of the essays that Downing and Clancy contributed to this book and of the present chapter.