[PDF] Top 20 Error Detection Using Linguistic Features

... of linguistic features into error de- tection: lexical features of words, and syn- tactic features from a robust lexicalized ...guistic features alone are not as useful as word ... See full document

... Automatic error detection is desired in the post-processing to improve machine translation ...system-based features, such as word posterior probabilities calculated from N- best lists or word ...of ... See full document

... We will focus our analysis on the first model, given that its result is perhaps most surprising. We observed that exclamation and question marks were present in non-hyperpartisan and mainstream articles, but a high ... See full document

... about error potentials in features from different domains and avoid overfitting caused by features of multiple dimensionalities, we proposed a new approach of combining multiple-channel ... See full document

... them using small set of expert ...method using the EM algorithm without any gold data: they first initialize the correct rating for each task based on the majority vote outcome, then estimated the quality ... See full document

... weighted features (learned by MEM) for each feature set for deceptive opinion and truthful opinion are listed in Table ...opinion detection meaning that truth authors can sometimes give concrete examples to ... See full document

... Therefore, detection of Alzheimer’s disease using speech-based features is gaining increasing ...of features based on speech prosody as well as linguistic features derived from ... See full document

... Traditionally least squares algorithms are used for form tolerance assessment. Form tolerances like flatness, cylindricity, perpendicularity can be assessed using this algorithm. The proposed approach applies to a ... See full document

... As multiword expressions (MWEs) exhibit a range of idiosyncrasies, their automatic detection warrants the use of many differ- ent features. Tsvetkov and Wintner (2014) proposed a Bayesian network model that ... See full document

... Such linguistic ambiguity has been reported in many annotation projects involving various linguistic phenomenon, such as the coreference relations, the predicate-argument structure, the semantic roles and ... See full document

... We propose a joint learning framework for emo- tion detection built on a convolutional encoder (CNN). We introduce a joint learning objective where the network needs to learn the (1) utter- ance text (the data ... See full document

... level features to detect the satire, which could be ...level linguistic features to unveil the satire by incorporating neural network and atten- tion ...paragraph-level features and ... See full document

... To evaluate parser performance on ESL data, we manually inspected the phrase structure trees and dependency graphs produced by the Stanford parser for 210 ESL sentences, split into 3 groups: the sentences in the first ... See full document

... A closer look at the score distribution (Figure 2) reveals our models had some difficulty predicting scores in the 1-2 range, possibly affected by the lower proportion of these cases in the training data. In addition, it ... See full document

... In digital communication, errors are introduced during the transmittal of data from sender to receiver due to interference or noise. Fault is a circumstance when the output information does not correspond with the input ... See full document

... The use of a large-scale learner corpus on gram- matical error correction is described in works such as Xie et al. (2016) and Chollampatt et al. (2016a,b). These studies used the Lang-8 corpus as training data for ... See full document

... the linguistic features for topic tracking, since both topic and event are related to a specific place and time in a ...generated using headline generation ... See full document

... performed using the approx- imate randomization procedure (Noreen, ...contextual features and dictionary lookup features are statistically signif- ...pendency features are statistically ... See full document

... the linguistic criteria that differentiate between the discourse of truth and of deception in the Hebrew language, and attempt to produce a primary test of the cognitive and emotional functions involved in the ... See full document

... Tense and aspect have been one of the most intriguing language issues when comparison is made in different languages. The reason for this is that languages do not always share the same linguistic background. This ... See full document