[PDF] Top 20 Measuring Feature Diversity in Native Language Identification

... Second Language Acquisition (SLA) investigate the multiplex of factors that influence our ability to acquire new languages and chief among these is the role of the learner’s mother ...of Native ... See full document

... In the most informative features for French, for example, we find developp from the French d´evelopp´e which leads to a misspelling of the En- glish word developed. In Arabic we observed a number of features that ... See full document

... the feature types used until that ...using language models for this task and in their system used language model perplexity scores based on lexical 5-grams from each language in the ...all ... See full document

... any of the previous NLI studies that had examined the same number (Bykh and Meurers, 2012) or even a smaller number of L1s in the ICLE (e.g., Koppel et al., 2005, Tsur and Rappoport, 2007; Bestgen et al., 2012). The only ... See full document

... also on the test set from the 2013 shared task, shown in Table 2. For both Tables 2 and 3 we report a random baseline and the best performances on the Shared Task: the first number is the top performer from the shared ... See full document

... the native language of an author based on texts written in a second language has generally been tackled as a clas- sification problem, typically using as features a mix of n-grams over characters and ... See full document

... We explore the performance of different feature types for NLI in this work. Among the features types we examine, character/word/lemma/stem n- grams have the best individual performance. De- pendency parses are ... See full document

... We excluded from our system individual features that did not perform well in our experiments. It would be helpful to evaluate the influence of these less accurate features and determine whether they would be useful to ... See full document

... The current state of the art in NLI, according to Malmasi and Dras (2017), utilizes some variant of contemporary machine learning classifier with the following types of features: (i) word, lemma and character n-grams, ... See full document

... Native Language Identification (NLI) is the task of automatically predicting the native language (L1) of a speaker given an unlabeled artifact such as a writing sample or speech ... See full document

... On the ICLE-NLI corpus, our best ensemble model achieves an accuracy of 90.1% for a 7-way classification task. This is substantially higher than any previously reported results on the ICLE. Note that our experiments were ... See full document

... Together with part-of-speech, character-level fea- tures are a commonly used feature for NLI (Mal- masi, 2016). Upon manual inspection of the essays and speech transcriptions corpora of the shared task, it became ... See full document

... of feature set size has proved to be a useful strategy for NLI (Jarvis et ...the feature set by approximately 90% of the origi- ...our feature set is ... See full document

... Before committing to analyzing emotion fea- tures, we want to test whether emotion-loaded words have any impact on the NLI task. The bag- of-words (BoW) representation covers a variety of phenomena, without ... See full document

... on which word-based approaches typically suffer. The downside is the need to index many ngrams. This is partly offset by 1) the fact that the number of actually observed ngrams grows much slower than the number of ... See full document

... Syntactic features, in contrast, in particular those that capture grammatical errors, which might po- tentially be useful for this task, have received lit- tle attention. Koppel et al. (2005) did suggest using syntactic ... See full document

... ral language such as words, phrases, or meaning, an approach that works at the character level has an important advantage in that it is language inde- pendent and linguistic theory ...for native ... See full document

... Table 1 contains the L1 classification results for the var- ious feature types and evaluation corpora. The boundary bigram and k-window collocations are obviously the most useful feature types; their ... See full document

... In addition to applications in forensic linguis- tics, Arabic NLI can aid the development of re- search tools for SLA researchers investigating lan- guage transfer and cross-linguistic effects. Simi- lar data-driven ... See full document

... all feature repre- sentations which are comparable across the different settings we uniformly scale all values employing the -Z option of ...freq feature representation based on the raw frequencies in ... See full document