Grapho-morphological awareness in Spanish L2 reading

This paper contributes to the literature on the transferability of grapho-morphological awareness (GMA) for L2 learners by analyzing L2 learners' morphology knowledge at the word and text level. GMA helps readers to identify grammatical categories, infer meanings of unfamiliar words, and access stored lexical information (Koda, 2008). Previous research indicates that L2 GMA is influenced by L1 GMA (Fender 2003; Hancin-Bhatt & Nagy, 1994; Koda, 2000; Ramirez, et. al., 2010; Schiff & Calif, 2007).In this paper, native speakers of Spanish (n=30) and native speakers of English learning Spanish as an L2 (n=46) completed four tasks: two timed lexical decision tasks (LDT) in English (only English speakers) and Spanish; three short passages followed by multiple choice questions; a cloze task; and an interview to discuss their answers. L2 learners show a native-like word recognition pattern (Clahsen & Felser, 2006a, 2006b), providing evidence for a language-specific morphological processing. L2 learners could recognize and decompose words into morphemes and lexemes through the different tasks, which implies that they neither ignore morphology nor follow a whole-word reading approach. However, this ability did not always help them to access the right word meaning. Also, orthographically similar words from L1 and L2 interfere with word recognition of inflected and derived words. Despite showing interference in inflected words during the timed LDT, they show a greater control during the interviews. However, derivational morphology is more difficult for L2 learners since they do not know derivational constraints either implicitly or explicitly. The results suggest that intermediate L2 learners with an alphabetic writing system in their L1 can go beyond transfer in an alphabetic L2, and that the relationship between proficiency and GMA might be reciprocal (Kuo & Anderson, 2008)

Autenttisiin teksteihin perustuva tietokoneavusteinen kielen oppiminen: sovelluksia italian kielelle

Computer-Assisted Language Learning (CALL) is one of the sub-disciplines within the area of Second Language Acquisition. Clozes, also called fill-in-the-blank, are largely used exercises in language learning applications. A cloze is an exercise where the learner is asked to provide a fragment that has been removed from the text. For language learning purposes, in addition to open-end clozes where one or more words are removed and the student must fill the gap, another type of cloze is commonly used, namely multiple-choice cloze. In a multiple-choice cloze, a fragment is removed from the text and the student must choose the correct answer from multiple options. Multiple-choice exercises are a common way of practicing and testing grammatical knowledge. The aim of this work is to identify relevant learning constructs for Italian to be applied to automatic exercises creation based on authentic texts in the Revita Framework. Learning constructs are units that represent language knowledge. Revita is a free to use online platform that was designed to provide language learning tools with the aim of revitalizing endangered languages including several Finno-Ugric languages such as North Saami. Later non-endangered languages were added. Italian is the first majority language to be added in a principled way. This work paves the way towards adding new languages in the future. Its purpose is threefold: it contributes to the raising of Italian from its beta status towards a full development stage; it formulates best practices for defining support for a new language and it serves as a documentation of what has been done, how and what remains to be done. Grammars and linguistic resources were consulted to compile an inventory of learning constructs for Italian. Analytic and pronominal verbs, verb government with prepositions, and noun phrase agreement were implemented by designing pattern rules that match sequences of tokens with specific parts-of-speech, surfaces and morphological tags. The rules were tested with test sentences that allowed further refining and correction of the rules. Current precision of the 47 rules for analytic and pronominal verbs on 177 test sentences results in 100%. Recall is 96.4%. Both precision and recall for the 5 noun phrase agreement rules result in 96.0% in respect to the 34 test sentences. Analytic and pronominal verb, as well as noun phrase agreement patterns, were used to generate open-end clozes. Verb government pattern rules were implemented into multiple-choice exercises where one of the four presented options is the correct preposition and the other three are prepositions that do not fit in context. The patterns were designed based on colligations, combinations of tokens (collocations) that are also explained by grammatical constraints. Verb government exercises were generated on a specifically collected corpus of 29074 words. The corpus included three types of text: biography sections from Wikipedia, Italian news articles and Italian language matriculation exams. The last text type generated the most exercises with a rate of 19 exercises every 10000 words, suggesting that the semi-authentic text met best the level of verb government exercises because of appropriate vocabulary frequency and sentence structure complexity. Four native language experts, either teachers of Italian as L2 or linguists, evaluated usability of the generated multiple-choice clozes, which resulted in 93.55%. This result suggests that minor adjustments i.e., the exclusion of target verbs that cause multiple-admissibility, are sufficient to consider verb government patterns usable until the possibility of dealing with multiple-admissible answers is addressed. The implementation of some of the most important learning constructs for Italian resulted feasible with current NLP tools, although quantitative evaluation of precision and recall of the designed rules is needed to evaluate the generation of exercises on authentic text. This work paves the way towards a full development stage of Italian in Revita and enables further pilot studies with actual learners, which will allow to measure learning outcomes in quantitative term

Empowering Expression for Users with Aphasia through Constrained Creativity

Creative activities allow people to express themselves in rich, nuanced ways. However, being creative does not always come easily. For example, people with speech and language impairments, such as aphasia, face challenges in creative activities that involve language. In this paper, we explore the concept of constrained creativity as a way of addressing this challenge and enabling creative writing. We report an app, MakeWrite, that supports the constrained creation of digital texts through automated redaction. The app was co-designed with and for people with aphasia and was subsequently explored in a workshop with a group of people with aphasia. Participants were not only successful in crafting novel language, but, importantly, self-reported that the app was crucial in enabling them to do so. We refect on the potential of technology-supported constrained creativity as a means of empowering expression amongst users with diverse needs

A Symbol of Uniqueness: The Cluster Bootstrap for the 3-Loop MHV Heptagon

Seven-particle scattering amplitudes in planar super-Yang-Mills theory are believed to belong to a special class of generalised polylogarithm functions called heptagon functions. These are functions with physical branch cuts whose symbols may be written in terms of the 42 cluster A-coordinates on Gr(4,7). Motivated by the success of the hexagon bootstrap programme for constructing six-particle amplitudes we initiate the systematic study of the symbols of heptagon functions. We find that there is exactly one such symbol of weight six which satisfies the MHV last-entry condition and is finite in the $7 \parallel 6$ collinear limit. This unique symbol is both dihedral and parity-symmetric, and remarkably its collinear limit is exactly the symbol of the three-loop six-particle MHV amplitude, although none of these properties were assumed a priori. It must therefore be the symbol of the three-loop seven-particle MHV amplitude. The simplicity of its construction suggests that the n-gon bootstrap may be surprisingly powerful for n>6.Comment: 30 pages, 3 ancillary files, v3: minor corrections, including a typo in (33

Modelling the formation of phonotactic restrictions across the mental lexicon

Experimental data shows that adult learners of an artificial language with a phonotactic restriction learned this restriction better when being trained on word types (e.g. when they were presented with 80 different words twice each) than when being trained on word tokens (e.g. when presented with 40 different words four times each) (Hamann & Ernestus submitted). These findings support Pierrehumbert’s (2003) observation that phonotactic co-occurrence restrictions are formed across lexical entries, since only lexical levels of representation can be sensitive to type frequencies

Quadrilateral-octagon coordinates for almost normal surfaces

Normal and almost normal surfaces are essential tools for algorithmic 3-manifold topology, but to use them requires exponentially slow enumeration algorithms in a high-dimensional vector space. The quadrilateral coordinates of Tollefson alleviate this problem considerably for normal surfaces, by reducing the dimension of this vector space from 7n to 3n (where n is the complexity of the underlying triangulation). Here we develop an analogous theory for octagonal almost normal surfaces, using quadrilateral and octagon coordinates to reduce this dimension from 10n to 6n. As an application, we show that quadrilateral-octagon coordinates can be used exclusively in the streamlined 3-sphere recognition algorithm of Jaco, Rubinstein and Thompson, reducing experimental running times by factors of thousands. We also introduce joint coordinates, a system with only 3n dimensions for octagonal almost normal surfaces that has appealing geometric properties.Comment: 34 pages, 20 figures; v2: Simplified the proof of Theorem 4.5 using cohomology, plus other minor changes; v3: Minor housekeepin