Automatic Error Detection

1976 ◽  
pp. 68-80 ◽  
Author(s):  
H. Kopetz
Keyword(s):  
Error Detection ◽  
Automatic Error

Automatic Error Detection

1979 ◽  
pp. 68-80
Author(s):  
H. Kopetz
Keyword(s):  
Error Detection ◽  
Automatic Error

scholarly journals A Probabilistic Approach to Error Detection&Correction for Tree-Mapping Grammars

2018 ◽  
Vol 111 (1) ◽  
pp. 97-112
Author(s):  
Tim vor der Brück
Keyword(s):  
Error Detection ◽  
Basic Assumption ◽  
Probabilistic Approach ◽  
Large Set ◽  
Generation Process ◽  
Input Structure ◽  
Error Detection And Correction ◽  
Complete Failure ◽  
Automatic Error

Abstract Rule-based natural language generation denotes the process of converting a semantic input structure into a surface representation by means of a grammar. In the following, we assume that this grammar is handcrafted and not automatically created for instance by a deep neural network. Such a grammar might comprise of a large set of rules. A single error in these rules can already have a large impact on the quality of the generated sentences, potentially causing even a complete failure of the entire generation process. Searching for errors in these rules can be quite tedious and time-consuming due to potentially complex and recursive dependencies. This work proposes a statistical approach to recognizing errors and providing suggestions for correcting certain kinds of errors by cross-checking the grammar with the semantic input structure. The basic assumption is the correctness of the latter, which is usually a valid hypothesis due to the fact that these input structures are often automatically created. Our evaluation reveals that in many cases an automatic error detection and correction is indeed possible.

Head and shoulders: automatic error detection in human-robot interaction

2017 ◽  
Author(s):  
Pauline Trung ◽  
Manuel Giuliani ◽  
Michael Miksch ◽  
Gerald Stollnberger ◽  
Susanne Stadler ◽  
...  
Keyword(s):  
Error Detection ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Automatic Error

ERROR DETECTION AND CORRECTION BASED ON CHINESE PHONEMIC ALPHABET IN CHINESE TEXT

2008 ◽  
Vol 16 (supp01) ◽  
pp. 89-105 ◽  
Author(s):  
CHUEN-MIN HUANG ◽  
MEI-CHEN WU ◽  
CHING-CHE CHANG
Keyword(s):  
Chinese Text ◽  
Error Detection ◽  
Experimental Results ◽  
Text Editor ◽  
Correction Rate ◽  
Error Detection And Correction ◽  
Chinese Texts ◽  
Chinese Writing ◽  
Automatic Error

Misspelling and misconception resulting from similar pronunciation appears frequently in Chinese texts. Without double check-up, this situation will be getting worse even with the help of Chinese input editor. It is hoped that the quality of Chinese writing would be enhanced if an effective automatic error detection and correction mechanism is embedded in text editor. Therefore, the burden of manpower to proofread shall be released. Until recently, researches in automatic error detection and correction of Chinese text have undergone many challenges and suffered from bad performance compared with that of Western text. In view of the prominent phenomenon in Chinese writing problem, this study proposes a learning model based on Chinese phonemic alphabets. The experimental results demonstrate that this model is effective in finding out misspellings and further improves detection and correction rate.

scholarly journals Revisit Automatic Error Detection for Wrong and Missing Translation – A Supervised Approach

2019 ◽  
Author(s):  
Wenqiang Lei ◽  
Weiwen Xu ◽  
Ai Ti Aw ◽  
Yuanxin Xiang ◽  
Tat Seng Chua
Keyword(s):  
Error Detection ◽  
Automatic Error
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