Automated assessment of non-native learner essays: Investigating the role of linguistic features

Automatic essay scoring (AES) refers to the process of scoring free text responses to given prompts, considering human grader scores as the gold standard. Writing such essays is an essential component of many language and aptitude exams. Hence, AES became an active and established area of research, and there are many proprietary systems used in real life applications today. However, not much is known about which specific linguistic features are useful for prediction and how much of this is consistent across datasets. This article addresses that by exploring the role of various linguistic features in automatic essay scoring using two publicly available datasets of non-native English essays written in test taking scenarios. The linguistic properties are modeled by encoding lexical, syntactic, discourse and error types of learner language in the feature set. Predictive models are then developed using these features on both datasets and the most predictive features are compared. While the results show that the feature set used results in good predictive models with both datasets, the question "what are the most predictive features?" has a different answer for each dataset.Comment: Article accepted for publication at: International Journal of Artificial Intelligence in Education (IJAIED). To appear in early 2017 (journal url: http://www.springer.com/computer/ai/journal/40593

Representation of Universal Quantifier in Bulgarian Language with Universal Networking Language

AbstractThe paper presents interpretation of universal quantifier in Bulgarian language with Universal Networking Language (UNL). It analyzes semantic and linguistic properties of universal quantifier and describes the parts of speech which function as quantifiers. In UNL frameworks they are presented as a lexical database with related grammar and semantic features using idea of synonymic semantic representation. The formal approach presented may be used also to language learning and understanding

Automated Adaptation Between Kiranti Languages

McCloy, Daniel, M.A., December 2006 Linguistics Automated Adaptation Between Kiranti Languages Chairperson: Dr. Anthony Mattina Minority language communities that are seeking to develop their language may be hampered by a lack of vernacular materials. Large volumes of such materials may be available in a related language. Automated adaptation holds potential to enable these large volumes of materials to be efficiently translated into the resource-scarce language. I describe a project to assess the feasibility of automatically adapting text between Limbu and Yamphu, two languages in Nepal’s Kiranti grouping. The approaches taken—essentially a transfer-based system partially hybridized with a Kiranti-specific interlingua—are placed in the context of machine translation efforts world-wide. A key principle embodied in this strategy is that adaptation can transcend the structural obstacles by taking advantage of functional commonalities. That is, what matters most for successful adaptation is that the languages “care about the same kinds of things.” I examine various typological phenomena of these languages to assess this degree of functional commonality. I look at the types of features marked on the finite verb, case-marking systems, the encoding of vertical deixis, object-incorporated verbs, and nominalization issues. As this Kiranti adaptation goal involves adaptation into multiple target languages, I also present a disambiguation strategy that ensures that the manual disambiguation performed for one target language is fed back into the system, such that the same disambiguation will not need to be performed again for other target languages

Interpersonality in ELF (Non)Academic Blogs: Self-mentions and Engagement Markers through Different Disciplines.

Abstract This study offers an analysis of interpersonality indicators, concretely self-mentions and engagement markers, in both academic and non-academic blogs belonging to four different disciplines, then consequently subjected to different conventions. In order to carry out this research, I have selected a corpus consisting of five blogs in ELF (English as a Lingua Franca) written by Spanish speakers, three of them non-academic – a cooking blog and two fashion blogs – and two of them academic – belonging to the fields of biology and psychology. The analysis of the results has been completed using Hyland’s metadiscourse paradigm (2005), exploring the frequency of appearance of self-mentions and engagement markers in each corpus. Resumen Este estudio pretende analizar los indicadores de interpersonalidad, más concretamente las auto-menciones del autor y las marcas de inclusión del lector, en varios blogs tanto académicos como no académicos pertenecientes a cuatro disciplinas diferentes, y por tanto sujetos a distintas convenciones. Para llevar a cabo el estudio, se ha seleccionado un corpus de cinco blogs en ELF (inglés como lengua franca) escritos por hablantes del español, tres de los cuales no son académicos – un blog sobre cocina y dos blogs sobre moda – y dos de los cuales sí son académicos – pertenecientes a los campos de la biología y la psicología. El análisis de los resultados se ha producido usando el paradigma de metadiscurso de Hyland (2005), observando la frecuencia de aparición de las auto-menciones y de las inclusiones del lector en cada uno de los corpus.<br /

NLization of Nouns, Pronouns and Prepositions in Punjabi With EUGENE

Abstract Universal Networking Language (UNL) has been used by various researchers as an Interlingua approach for AMT (Automatic machine translation). The UNL system consists of two main components/tools, namely, EnConverter-IAN (used for converting the text from a source language to UNL) and DeConverter -EUGENE (used for converting the text from UNL to a target language). This paper highlights the DeConversion generation rules used for the DeConverter and indicates its usage in the generation of Punjabi sentences. This paper also covers the results of implementation of UNL input by using DeConverter-EUGENE and its evaluation on UNL sentences such as Nouns, Pronouns and Prepositions

Con[Text]

My work explores the relationship of text and image to the creation and perception of our roles in the world, principally from a feminist point of view. I examine the influence of symbols and labels, both imposed and carefully chosen, on the identity women present to the world and ourselves. Through photography and design, I reflect on the roles I fill in my own life as an artist, wife, mother, and daughter and the symbols and words associated with such roles in the hope of revealing a larger truth about communication and relationships through words and images

ANNOTATED DISJUNCT FOR MACHINE TRANSLATION

Most information found in the Internet is available in English version. However, most people in the world are non-English speaker. Hence, it will be of great advantage to have reliable Machine Translation tool for those people. There are many approaches for developing Machine Translation (MT) systems, some of them are direct, rule-based/transfer, interlingua, and statistical approaches. This thesis focuses on developing an MT for less resourced languages i.e. languages that do not have available grammar formalism, parser, and corpus, such as some languages in South East Asia. The nonexistence of bilingual corpora motivates us to use direct or transfer approaches. Moreover, the unavailability of grammar formalism and parser in the target languages motivates us to develop a hybrid between direct and transfer approaches. This hybrid approach is referred as a hybrid transfer approach. This approach uses the Annotated Disjunct (ADJ) method. This method, based on Link Grammar (LG) formalism, can theoretically handle one-to-one, many-to-one, and many-to-many word(s) translations. This method consists of transfer rules module which maps source words in a source sentence (SS) into target words in correct position in a target sentence (TS). The developed transfer rules are demonstrated on English → Indonesian translation tasks. An experimental evaluation is conducted to measure the performance of the developed system over available English-Indonesian MT systems. The developed ADJ-based MT system translated simple, compound, and complex English sentences in present, present continuous, present perfect, past, past perfect, and future tenses with better precision than other systems, with the accuracy of 71.17% in Subjective Sentence Error Rate metric