[PDF] Top 20 Native Language Identification: A Key N gram Category Approach
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Native Language Identification: A Key N gram Category Approach
... across language groups (as suggested by Koppel et ...across language groups, raising the question of the degree to which the ob- served differences in texts were due to CLI, profi- ciency level, or essay ... See full document
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The Power of Character N grams in Native Language Identification
... NLI is typically framed as a multi-class classifi- cation problem, wherein a classifier is trained on more than two native languages simultaneously. As with many text-classification tasks, Support Vector Machines ... See full document
8
Native Language Identification using Recurring n grams – Investigating Abstraction and Domain Dependence
... Which language properties are the most appropriate ones to use as classifier features for the given task and can they reliably be identified? How well can a surface-based approach fare in the task and what ... See full document
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CIC FBK Approach to Native Language Identification
... Syntactic n-grams can be used in any task where traditional n-grams are ...Syntactic n-grams outper- formed traditional n-grams in the task of author- ship attribution (Sidorov et ...syntactic ... See full document
8
Can characters reveal your native language? A language independent approach to native language identification
... the approach based on string kernels performed so well, it remains to be further investigated why this is the case and why such a simple approach can compete with far more complex approaches that take ... See full document
11
Native Language Identification on Text and Speech
... Dialect Identification In the last few years, we observed a significant and important overlap between NLI approaches and computational methods applied to dialect, lan- guage variety, and similar language ... See full document
7
Native Language Identification Using a Mixture of Character and Word N grams
... simple N-gram- based methods as the implementation of these ap- proaches can be simpler and, as a result, less time- ...character n-grams, word n-grams, POS n-grams, and the perplexity ... See full document
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A Shallow Neural Network for Native Language Identification with Character N grams
... character n-grams features could effectively identify the native lan- guage (L1) of the ...character n- grams mostly works for any style-based classifica- tion tasks including ... See full document
6
Stacked Sentence Document Classifier Approach for Improving Native Language Identification
... In order to test the performances of the pro- posed two-stacked sentence-document classifier, we conducted several experiments exploiting dif- ferent configurations of our system. Table 1 reports the configurations ... See full document
8
Robust, Lexicalized Native Language Identification
... prototype approach to be able to better deal with the commonalities and differences among languages than the 1va, which lumps diverse languages into a single ‘other’ ... See full document
18
A study of N gram and Embedding Representations for Native Language Identification
... The last few years saw the field of NLI advance in both the directions of feature engineering and modeling. However, irrespective of what model- ing choices were made, results seem to show that word level features still ... See full document
9
Native Language Identification: a Simple n gram Based Approach
... same language family i.e. Indo-European/Romance and have a similar gram- matical ...English language is very strict in the order of words (Subject-Verb-Object), Spanish, Italian and French allow more ... See full document
8
Incremental N gram Approach for Language Identification in Code Switched Text
... a language is acquired or ...their native language as well as in ...certain language is more likely to be used than a word with the same meaning of another language and which languages ... See full document
6
The Role of Emotions in Native Language Identification
... Native Language Identification (NLI) is the task of identifying the native language (L1) of a person based on his/her writing in the second language ... See full document
7
A Portuguese Native Language Identification Dataset
... • Grammatical error detection and correction: as discussed in Zampieri and Tan (2014), a known challenge in this task is acquiring suit- able training data to account for the vari- ation of errors present in ... See full document
6
Secure Bio-Cryptographic Authentication System for Cardless Automated Teller Machines
... Several approaches were proposed for Arabic TC using Naïve Bayes algorithm [17], KNN [16,18-22], SVM [9,19-27], Decision Tree [9,28- 30], Manhattan Distance and Dice Measures [15], Polynomial Neural Networks (PNNs) [5], ... See full document
10
Federated Learning of N Gram Language Models
... quality n-gram language models using feder- ated ...virtual key- boards, because training is performed with- out the users’ data ever leaving their ...by n-gram language ... See full document
10
A Character n gram Based Approach for Improved Recall in Indian Language NER
... The state-of-art techniques for Indic lan- guages(Telugu and Hindi) use word based models which suffer from low recall, use gazetteers and are language dependent. As such there is no NER system for Telugu. ... See full document
8
Ensemble Methods for Native Language Identification
... as n-gram order increases (see Table ...higher-order n-grams (Jarvis et ...word n-grams at the bigram level, where accuracy drops for word ... See full document
7
N gram Language Models and POS Distribution for the Identification of Spanish Varieties (Ngrammes et Traits Morphosyntaxiques pour la Identification de Variétés de l’Espagnol) [in French]
... Ngrammes et Traits Morphosyntaxiques pour la Identification de Variétés de l’Espagnol Notre article présente expérimentations portant sur la classification supervisée de variétés nationales de l’espagnol. Outre ... See full document
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