[PDF] Top 20 Unifying Human and Statistical Evaluation for Natural Language Generation
Has 10000 "Unifying Human and Statistical Evaluation for Natural Language Generation" found on our website. Below are the top 20 most common "Unifying Human and Statistical Evaluation for Natural Language Generation".
Unifying Human and Statistical Evaluation for Natural Language Generation
... modeling, a model that directly plagiarizes sen- tences from the training set would pass the hu- man quality bar but would have zero generaliza- tion ability and thus have inadequate diversity. On the other hand, ... See full document
13
The use of rating and Likert scales in Natural Language Generation human evaluation tasks: A review and some recommendations
... Rating and Likert scales are popular tools used in surveys to estimate feeling, opinions or atti- tudes of responders. Although both instruments are widely used, their nature and their appropriate statistical ... See full document
6
A Repository of Data and Evaluation Resources for Natural Language Generation
... Evaluation: For the TUNA - AS task, we developed a Java program that, given a corpus of TUNA instances, computes (i) two coefficients, Dice and MASI (Passonneau, 2006) that assessed the degree of overlap between ... See full document
6
Exploiting Ontology Lexica for Generating Natural Language Texts from RDF Data
... principled natural lan- guage generation architecture that follows a classical NLG architecture but exploits an on- tology lexicon as well as statistical information derived from a domain corpus in ... See full document
10
Text Content and Task Performance in the Evaluation of a Natural Language Generation System
... and human-authored (H) texts in terms of ...second evaluation measure quan- tified the extent to which a text was relevant to the appro- priate actions on a given ... See full document
6
Evaluation of SPARQL query generation from natural language questions
... inal natural language question. (Yahya et al., 2012) used two human judges to manually exam- ine the output of their system at three points— disambiguation, SPARQL query construction, and the answers ... See full document
5
RankME: Reliable Human Ratings for Natural Language Generation
... To obtain more insight into informativeness rat- ings, we asked crowd workers to further distinguish informativeness in terms of added and missed in- formation with respect to the original MR. Crowd workers were asked to ... See full document
7
Natural Language Generation enhances human decision making with uncertain information
... into language (Power and Williams, 2012) and the use of vague ex- pressions (van Deemter, ...into Natural Language so as to maximise confidence and correct outcomes of hu- man ...based ... See full document
5
Human like Natural Language Generation Using Monte Carlo Tree Search
... is natural for us because the result cannot be naturally represented by a win or a ...is natural or ...two evaluation scores: one for syntactic structure and the other for the n-gram language ... See full document
8
Statistical Acquisition of Content Selection Rules for Natural Language Generation
... Our goal is to develop a system that can auto- matically acquire constraints for the content selec- tion task. Our algorithm uses the information we learned from a corpus of desired outputs for the sys- tem (i.e., ... See full document
8
Best practices for the human evaluation of automatically generated text
... Human evaluation of natural language generation systems can be done using intrinsic and extrinsic methods (Sparck Jones and Galliers, 1996; Belz and Reiter, ...extrinsic ... See full document
14
Statistical Natural Language Generation from Tabular Non textual Data
... existing natural language gener- ation (NLG) techniques employing statistical methods are typically resource and time in- ...significant human/designer ef- forts. In this paper, we proposed a ... See full document
10
Aggregation Improves Learning: Experiments in Natural Language Generation for Intelligent Tutoring Systems
... Regarding the role of NL interfaces for ITSs, only very recently have the first few results become avail- able, to show that first of all, students do learn when interacting in NL with an ITS (Litman et al., 2004; ... See full document
8
Towards Automatic Generation of Natural Language Generation Systems
... a human-human corpus of dialogs (HH) from Carnegie Mellon ...because human-human interaction differs from human-computer interaction which is our true target ... See full document
7
Semi Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
... Results of the human experiment are reported in Table 4. The first line reports the results of the reference (i.e., the Wikipedia abstract) for com- parison, while the second line is the model with paired data, ... See full document
11
Task demands and individual variation in referring expressions
... the human-likeness of nat- ural language generation systems, this study investigates different sources of variation that might influence the production of referring expressions (REs), namely the ... See full document
5
Natural Language Input for Scene Generation
... the object in terms of prototype THOUGHTs.. divided in different levels of detail hier-.[r] ... See full document
8
Scaling a Natural Language Generation System
... pipeline generation is inte- grated generation, in which the sentence plan- ning and surface realization tasks happen simul- taneously (Reiter and Dale, ...integrated generation by ... See full document
10
Natural Language Generation from Pictographs
... Table 1 shows the respective BLEU, NIST (Doddington, 2002), and Word Error Rate (WER) scores for the translation of messages into Sclera and into Beta. We use these metrics to present improvements over the baseline. As ... See full document
5
Related subjects