A Comparative Study of English Word Order Acquisition by Elementary and Secondary School Pupils - Native Speakers of Serbian and Hungarian

Kitic investigated the phenomenon of English word order acquisition by Serbian and Hungarian speakers, examining both the theoretical and empirical aspects of this phenomenon. She began by looking at language learning and language acquisition, viewing word order acquisition in the context of relevant linguistic and psycholinguistic knowledge. The main hypothesis of her empirical investigation was that the majority of word order mistakes in the language production of Serbian and Hungarian speakers of English is due to mother tongue interference. Three supporting hypotheses were introduced to specify the phenomenon of interference in its correlation to (1) language proficiency, (2) sentence patterns, and (3) optional adverbials. The conclusions were based on error analysis of 9280 sentences of 464 elementary and high school learners. The results showed that a learner's level of proficiency seems to be a relevant factor in mother tongue interference as this decreases with increased proficiency. Word order errors are however fossilised at the highest levels. The causes of interference errors, which increase with the number of sentence elements, are either absent sentence patterns or similar ones. In the case of adverbials, word order errors have two forms: interrelation (with canonical elements) and mixed adverbials.

A Robust Parser of Czech

Mr. Kubon's project was inspired by the growing need for an automatic, syntactic analyser (parser) of Czech, which could be used in the syntactic processing of large amounts of texts. Mr. Kubon notes that such a tool would be very useful, especially in the field of corpus linguistics, where creating a large-scale "tree bank" (a collection of syntactic representations of natural language sentences) is a very important step towards the investigation of the properties of a given language. The work involved in syntactically parsing a whole corpus in order to get a representative set of syntactic structures would be almost inconceivable without the help of some kind of robust (semi)automatic parser. The need for the automatic natural language parser to be robust increases with the size of the linguistic data in the corpus or in any other kind of text which is going to be parsed. Practical experience shows that apart from syntactically correct sentences, there are many sentences which contain a "real" grammatical error. These sentences may be corrected in small-scale texts, but not generally in the whole corpus. In order to be able to complete the overall project, it was necessary to address a number of smaller problems. These were; 1. the adaptation of a suitable formalism able to describe the formal grammar of the system; 2. the definition of the structure of the system's dictionary containing all relevant lexico-syntactic information, and the development of a formal grammar able to robustly parse Czech sentences from the test suite; 3. filling the syntactic dictionary with sample data allowing the system to be tested and debugged during its development (about 1000 words); 4. the development of a set of sample sentences containing a reasonable amount of grammatical and ungrammatical phenomena covering some of the most typical syntactic constructions being used in Czech. Number 3, building a formal grammar, was the main task of the project. The grammar is of course far from complete (Mr. Kubon notes that it is debatable whether any formal grammar describing a natural language may ever be complete), but it covers the most frequent syntactic phenomena, allowing for the representation of a syntactic structure of simple clauses and also the structure of certain types of complex sentences. The stress was not so much on building a wide coverage grammar, but on the description and demonstration of a method. This method uses a similar approach as that of grammar-based grammar checking. The problem of reconstructing the "correct" form of the syntactic representation of a sentence is closely related to the problem of localisation and identification of syntactic errors. Without a precise knowledge of the nature and location of syntactic errors it is not possible to build a reliable estimation of a "correct" syntactic tree. The incremental way of building the grammar used in this project is also an important methodological issue. Experience from previous projects showed that building a grammar by creating a huge block of metarules is more complicated than the incremental method, which begins with the metarules covering most common syntactic phenomena first, and adds less important ones later, especially from the point of view of testing and debugging the grammar. The sample of the syntactic dictionary containing lexico-syntactical information (task 4) now has slightly more than 1000 lexical items representing all classes of words. During the creation of the dictionary it turned out that the task of assigning complete and correct lexico-syntactic information to verbs is a very complicated and time-consuming process which would itself be worth a separate project. The final task undertaken in this project was the development of a method allowing effective testing and debugging of the grammar during the process of its development. The problem of the consistency of new and modified rules of the formal grammar with the rules already existing is one of the crucial problems of every project aiming at the development of a large-scale formal grammar of a natural language. This method allows for the detection of any discrepancy or inconsistency of the grammar with respect to a test-bed of sentences containing all syntactic phenomena covered by the grammar. This is not only the first robust parser of Czech, but also one of the first robust parsers of a Slavic language. Since Slavic languages display a wide range of common features, it is reasonable to claim that this system may serve as a pattern for similar systems in other languages. To transfer the system into any other language it is only necessary to revise the grammar and to change the data contained in the dictionary (but not necessarily the structure of primary lexico-syntactic information). The formalism and methods used in this project can be used in other Slavic languages without substantial changes.

Semiotic Analysis in the Study of Social Work

Research and professional practices have the joint aim of re-structuring the preconceived notions of reality. They both want to gain the understanding about social reality. Social workers use their professional competence in order to grasp the reality of their clients, while researchers’ pursuit is to open the secrecies of the research material. Development and research are now so intertwined and inherent in almost all professional practices that making distinctions between practising, developing and researching has become difficult and in many aspects irrelevant. Moving towards research-based practices is possible and it is easily applied within the framework of the qualitative research approach (Dominelli 2005, 235; Humphries 2005, 280). Social work can be understood as acts and speech acts crisscrossing between social workers and clients. When trying to catch the verbal and non-verbal hints of each others’ behaviour, the actors have to do a lot of interpretations in a more or less uncertain mental landscape. Our point of departure is the idea that the study of social work practices requires tools which effectively reveal the internal complexity of social work (see, for example, Adams & Dominelli & Payne 2005, 294 – 295). The boom of qualitative research methodologies in recent decades is associated with much profound the rupture in humanities, which is called the linguistic turn (Rorty 1967). The idea that language is not transparently mediating our perceptions and thoughts about reality, but on the contrary it constitutes it was new and even confusing to many social scientists. Nowadays we have got used to read research reports which have applied different branches of discursive analyses or narratologic or semiotic approaches. Although differences are sophisticated between those orientations they share the idea of the predominance of language. Despite the lively research work of today’s social work and the research-minded atmosphere of social work practice, semiotics has rarely applied in social work research. However, social work as a communicative practice concerns symbols, metaphors and all kinds of the representative structures of language. Those items are at the core of semiotics, the science of signs, and the science which examines people using signs in their mutual interaction and their endeavours to make the sense of the world they live in, their semiosis. When thinking of the practice of social work and doing the research of it, a number of interpretational levels ought to be passed before reaching the research phase in social work. First of all, social workers have to interpret their clients’ situations, which will be recorded in the files. In some very rare cases those past situations will be reflected in discussions or perhaps interviews or put under the scrutiny of some researcher in the future. Each and every new observation adds its own flavour to the mixture of meanings. Social workers have combined their observations with previous experience and professional knowledge, furthermore, the situation on hand also influences the reactions. In addition, the interpretations made by social workers over the course of their daily working routines are never limited to being part of the personal process of the social worker, but are also always inherently cultural. The work aiming at social change is defined by the presence of an initial situation, a specific goal, and the means and ways of achieving it, which are – or which should be – agreed upon by the social worker and the client in situation which is unique and at the same time socially-driven. Because of the inherent plot-based nature of social work, the practices related to it can be analysed as stories (see Dominelli 2005, 234), given, of course, that they are signifying and told by someone. The research of the practices is concentrating on impressions, perceptions, judgements, accounts, documents etc. All these multifarious elements can be scrutinized as textual corpora, but not whatever textual material. In semiotic analysis, the material studied is characterised as verbal or textual and loaded with meanings. We present a contribution of research methodology, semiotic analysis, which has to our mind at least implicitly references to the social work practices. Our examples of semiotic interpretation have been picked up from our dissertations (Laine 2005; Saurama 2002). The data are official documents from the archives of a child welfare agency and transcriptions of the interviews of shelter employees. These data can be defined as stories told by the social workers of what they have seen and felt. The official documents present only fragmentations and they are often written in passive form. (Saurama 2002, 70.) The interviews carried out in the shelters can be described as stories where the narrators are more familiar and known. The material is characterised by the interaction between the interviewer and interviewee. The levels of the story and the telling of the story become apparent when interviews or documents are examined with the use of semiotic tools. The roots of semiotic interpretation can be found in three different branches; the American pragmatism, Saussurean linguistics in Paris and the so called formalism in Moscow and Tartu; however in this paper we are engaged with the so called Parisian School of semiology which prominent figure was A. J. Greimas. The Finnish sociologists Pekka Sulkunen and Jukka Törrönen (1997a; 1997b) have further developed the ideas of Greimas in their studies on socio-semiotics, and we lean on their ideas. In semiotics social reality is conceived as a relationship between subjects, observations, and interpretations and it is seen mediated by natural language which is the most common sign system among human beings (Mounin 1985; de Saussure 2006; Sebeok 1986). Signification is an act of associating an abstract context (signified) to some physical instrument (signifier). These two elements together form the basic concept, the “sign”, which never constitutes any kind of meaning alone. The meaning will be comprised in a distinction process where signs are being related to other signs. In this chain of signs, the meaning becomes diverged from reality. (Greimas 1980, 28; Potter 1996, 70; de Saussure 2006, 46-48.) One interpretative tool is to think of speech as a surface under which deep structures – i.e. values and norms – exist (Greimas & Courtes 1982; Greimas 1987). To our mind semiotics is very much about playing with two different levels of text: the syntagmatic surface which is more or less faithful to the grammar, and the paradigmatic, semantic structure of values and norms hidden in the deeper meanings of interpretations. Semiotic analysis deals precisely with the level of meaning which exists under the surface, but the only way to reach those meanings is through the textual level, the written or spoken text. That is why the tools are needed. In our studies, we have used the semiotic square and the actant analysis. The former is based on the distinctions and the categorisations of meanings, and the latter on opening the plotting of narratives in order to reach the value structures.

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

What do we mean by Female and Male in Neurocognitive Experiments on Language?

For several years now, neuroscientific research has been striving towards fundamental answers to questions about the relevance of sex/gender to language processing in the brain. This research has been effected through the search for sex/gender differences in the neurobiology of language processing. Thus, the main aim has ever been to focus on the differentiation of the sexes/genders, failing to define what sex, what gender, what female or male is in neurolingustic research. In other words, although neuroscientific findings have provided key insights into the brain functioning of women and men, neuropsychology has rarely questioned the complexity of the sex/gender variable beyond biology. What does “female” or “male” mean in human neurocognition; how are operationalisations implemented along the axes of “femaleness” or “maleness”; or what biological evidence is used to register the variables sex and/or gender? In the neurosciences as well as in neurocognitive research, questions such as these have so far not been studied in detail, even if they are highly significant for the scientific process. Instead, the variable of sex/gender has always been thought as solely dichotomous (as either female or male), oppositional and exclusionary of each other. Here, this theoretical contribution sets in. Based on findings in neuroscience and concepts in gender theory, this poster is dedicated to the reflection about what sex/gender is in the neuroscience of language processing. Following this aim, two levels of interest will be addressed. First: How do we define sex/gender at the level of participants? And second: How do we define sex/gender at the level of the experimental task? For the first, a multifactorial registration (work in progress) of the variable sex/gender will be presented, i.e. a tool that records sex/gender in terms of biology and social issues as well as on a spectrum between femaleness and maleness. For the second, the compulsory dichotomy of a gendered task when neurolinguistically approaching our cognitions of sex/gender will be explored.

Language lateralisation increases with age in very preterm born 7-12 year-olds but not in term born control children

Background: Neural structural abnormalities as well as cognitive difficulties in language processing have been described in children born very preterm (<32 weeks of gestational age and/or <1500 g birth weight). These findings raise the question how premature birth is related to neural language organisation and lateralisation. The aim of the study was to test the following hypotheses: a) VPT/VLBW and control children show different language organisation b) language organisation in VPT/VLBW children is more bilateral compared to language organisation in control children c) positive correlations between language performance measures and language lateralisation exist in VPT/VLBW children and controls. Method: Brain activity was measured during a phonologic detection task in 56 very preterm born children and 38 term born control children aged 7 to 12 years using functional Magnetic Resonance Imaging. General IQ, verbal IQ, verbal fluency and reading comprehension were assessed outside the scanner. Results: Language organisation and lateralisation did not differ in very preterm and control children in overall comparisons. However, in very preterm children lateralisation increased between the age of 7 to 12 years. This correlation was not found in control children. Language organisation in very preterm children was bilateral in young children and left-sided in old children, whereas language organisation in control children was left-sided in the young and old age group. Frontal lateralisation correlated with General IQ in controls, but no other correlations between lateralisation and verbal performance were found. Discussion: The results of this study suggest different developmental patterns of language processing in very preterm born and term born control children. While very preterm born children showed atypical language organisation and lateralisation in younger years, typical left-sided patterns were found at the age of 12 years.

Semantic, perceptual and number space: relations between category width and spatial processing.

Coarse semantic encoding and broad categorization behavior are the hallmarks of the right cerebral hemisphere's contribution to language processing. We correlated 40 healthy subjects' breadth of categorization as assessed with Pettigrew's category width scale with lateral asymmetries in perceptual and representational space. Specifically, we hypothesized broader category width to be associated with larger leftward spatial biases. For the 20 men, but not the 20 women, this hypothesis was confirmed both in a lateralized tachistoscopic task with chimeric faces and a random digit generation task; the higher a male participant's score on category width, the more pronounced were his left-visual field bias in the judgement of chimeric faces and his small-number preference in digit generation ("small" is to the left of "large" in number space). Subjects' category width was unrelated to lateral displacements in a blindfolded tactile-motor rod centering task. These findings indicate that visual-spatial functions of the right hemisphere should not be considered independent of the same hemisphere's contribution to language. Linguistic and spatial cognition may be more tightly interwoven than is currently assumed.

Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

Evaluating a Speech Communication System for deaf people

This paper describes the development of an Advanced Speech Communication System for Deaf People and its field evaluation in a real application domain: the renewal of Driver’s License. The system is composed of two modules. The first one is a Spanish into Spanish Sign Language (LSE: Lengua de Signos Española) translation module made up of a speech recognizer, a natural language translator (for converting a word sequence into a sequence of signs), and a 3D avatar animation module (for playing back the signs). The second module is a Spoken Spanish generator from sign-writing composed of a visual interface (for specifying a sequence of signs), a language translator (for generating the sequence of words in Spanish), and finally, a text to speech converter. For language translation, the system integrates three technologies: an example-based strategy, a rule-based translation method and a statistical translator. This paper also includes a detailed description of the evaluation carried out in the Local Traffic Office in the city of Toledo (Spain) involving real government employees and deaf people. This evaluation includes objective measurements from the system and subjective information from questionnaires. Finally, the paper reports an analysis of the main problems and a discussion about possible solutions.

Source Language Categorization for improving a Speech into Sign Language Translation System

This paper describes a categorization module for improving the performance of a Spanish into Spanish Sign Language (LSE) translation system. This categorization module replaces Spanish words with associated tags. When implementing this module, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not relevant in the translation process. The categorization module has been incorporated into a phrase-based system and a Statistical Finite State Transducer (SFST). The evaluation results reveal that the BLEU has increased from 69.11% to 78.79% for the phrase-based system and from 69.84% to 75.59% for the SFST.

Estudio cinemático del cuerpo humano mediante Kinect

La cámara Kinect está desarrollada por Prime Sense en colaboración con Microsoft para la consola XBox, ofrece imágenes de profundidad gracias a un sensor infrarrojo. Este dispositivo también incluye una cámara RGB que ofrece imágenes a color además de una serie de micrófonos colocados de tal manera que son capaces de saber de qué ángulo proviene el sonido. En un principio Kinect se creó para el ocio doméstico pero su bajo precio (en comparación con otras cámaras de iguales características) y la aceptación por parte de desarrolladores han explotado sus posibilidades. El objetivo de este proyecto es, partiendo de estos datos, la obtención de variables cinemáticas tales como posición, velocidad y aceleración de determinados puntos de control del cuerpo de un individuo como pueden ser el cabeza, cuello, hombros, codos, muñecas, caderas, rodillas y tobillos a partir de los cuales poder extraer patrones de movimiento. Para ello se necesita un middleware mediante el entorno de libre distribución (GNU) multiplataforma. Como IDE se ha utilizado Processing, un entorno open source creado para proyectos de diseño. Además se ha utilizado el contenedor SimpleOpenNI, desarrollado por estudiantes e investigadores que trabajan con Kinect. Esto ofrece la posibilidad de prescindir del SDK de Microsoft, el cual es propietario y obliga a utilizar su sistema operativo, Windows. Usando estas herramientas se consigue una solución viable para varios sistemas operativos. Se han utilizado métodos y facilidades que ofrece el lenguaje orientado a objetos Java (Proccesing hereda de este), y se ha planteado una solución basada en un modelo cliente servidor que dota de escalabilidad al proyecto. El resultado del proyecto es útil en aplicaciones para poblaciones con riesgo de exclusión (como es el espectro autista), en telediagnóstico, y en general entornos donde se necesite estudiar hábitos y comportamientos a partir del movimiento humano. Con este proyecto se busca tener una continuidad mediante otras aplicaciones que analicen los datos ofrecidos. ABSTRACT. The Kinect camera is developed by PrimeSense in collaboration with Microsoft for the xBox console provides depth images thanks to an infrared sensor. This device also includes an RGB camera that provides color images in addition to a number of microphones placed such that they are able to know what angle the sound comes. Kinect initially created for domestic leisure but its low prices (compared to other cameras with the same characteristics) and acceptance by developers have exploited its possibilities. The objective of this project is based on this data to obtain kinematic variables such as position, velocity and acceleration of certain control points of the body of an individual from which to extract movement patterns. These points can be the head, neck, shoulders, elbows, wrists, hips, knees and ankles. This requires a middleware using freely distributed environment (GNU) platform. Processing has been used as a development environment, and open source environment created for design projects. Besides the container SimpleOpenNi has been used, it developed by students and researchers working with Kinect. This offers the possibility to dispense with the Microsoft SDK which owns and agrees to use its operating system, Windows. Using these tools will get a viable solution for multiple operating systems. We used methods and facilities of the Java object-oriented language (Processing inherits from this) and has proposed a solution based on a client-server model which provides scalability to the project. The result of the project is useful in applications to populations at risk of exclusion (such as autistic spectrum), in remote diagnostic, and in general environments that need study habits and behaviors from human motion. This project aims to have continuity using other applications to analyze the data provided.

Construcción automática de grafos RDF a partir de frases en lenguaje natural para la integración de bases de datos heterogéneas

El presente trabajo desarrolla un servicio REST que transforma frases en lenguaje natural a grafos RDF. Los grafos generados son grafos dirigidos, donde los nodos se forman con los sustantivos o adjetivos de las frases, y los arcos se forman con los verbos. Se utiliza dentro del proyecto p-medicine para dar soporte a las siguientes funcionalidades: Búsquedas en lenguaje natural: actualmente la plataforma p-medicine proporciona un interfaz programático para realizar consultas en SPARQL. El servicio desarrollado permitiría generar esas consultas automáticamente a partir de frases en lenguaje natural. Anotaciones de bases de datos mediante lenguaje natural: la plataforma pmedicine incorpora una herramienta, desarrollada por el Grupo de Ingeniería Biomédica de la Universidad Politécnica de Madrid, para la anotación de bases de datos RDF. Estas anotaciones son necesarias para la posterior traducción de las bases de datos a un esquema central. El proceso de anotación requiere que el usuario construya de forma manual las vistas RDF que desea anotar, lo que requiere mostrar gráficamente el esquema RDF y que el usuario construya vistas RDF seleccionando las clases y relaciones necesarias. Este proceso es a menudo complejo y demasiado difícil para un usuario sin perfil técnico. El sistema se incorporará para permitir que la construcción de estas vistas se realice con lenguaje natural. ---ABSTRACT---The present work develops a REST service that transforms natural language sentences to RDF degrees. Generated graphs are directed graphs where nodes are formed with nouns or adjectives of phrases, and the arcs are formed with verbs. Used within the p-medicine project to support the following functionality: Natural language queries: currently the p-medicine platform provides a programmatic interface to query SPARQL. The developed service would automatically generate those queries from natural language sentences. Memos databases using natural language: the p-medicine platform incorporates a tool, developed by the Group of Biomedical Engineering at the Polytechnic University of Madrid, for the annotation of RDF data bases. Such annotations are necessary for the subsequent translation of databases to a central scheme. The annotation process requires the user to manually construct the RDF views that he wants annotate, requiring graphically display the RDF schema and the user to build RDF views by selecting classes and relationships. This process is often complex and too difficult for a user with no technical background. The system is incorporated to allow the construction of these views to be performed with natural language.

Exploring cognition processes in second language acquisition: the case of cognates and false-friends in EST

This article explores one aspect of the processing perspective in L2 learning in an EST context: the processing of new content words, in English, of the type ‘cognates’ and ‘false friends’, by Spanish speaking engineering students. The paper does not try to offer a comprehensive overview of language acquisition mechanisms, but rather it is intended to review more narrowly how our conceptual systems, governed by intricately linked networks of neural connections in the brain, make language development possible, creating, at the same time, some L2 processing problems. The case of ‘cognates and false friends’ in specialised contexts is brought here to illustrate some of the processing problems that the L2 learner has to confront, and how mappings in the visual, phonological and semantic (conceptual) brain structures function in second language processing of new vocabulary. Resumen Este artículo pretende reflexionar sobre un aspecto de la perspectiva del procesamiento de segundas lenguas (L2) en el contexto del ICT: el procesamiento de palabras nuevas, en inglés, conocidas como “cognados” y “falsos amigos”, por parte de estudiantes de ingeniería españoles. No se pretende ofrecer una visión completa de los mecanismos de adquisición del lenguaje, más bien se intenta mostrar cómo nuestro sistema conceptual, gobernado por una complicada red de conexiones neuronales en el cerebro, hace posible el desarrollo del lenguaje, aunque ello conlleve ciertas dificultades en el procesamiento de segundas lenguas. El caso de los “cognados” y los “falsos amigos”, en los lenguajes de especialidad, se trae para ilustrar algunos de los problemas de procesamiento que el estudiante de una lengua extranjera tiene que afrontar y el funcionamiento de las correspondencias entre las estructuras visuales, fonológicas y semánticas (conceptuales) del cerebro en el procesamiento de nuevo vocabulario.

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Adaptación de una herramienta de Generación de Lenguaje Natural al idioma Español

En el presente Trabajo de Fin de Máster se ha realizado un análisis sobre las técnicas y herramientas de Generación de Lenguaje Natural (GLN), así como las modificaciones a la herramienta Simple NLG para generar expresiones en el idioma Español. Dicha extensión va a permitir ampliar el grupo de personas a las cuales se les transmite la información, ya que alrededor de 540 millones de personas hablan español. Keywords - Generación de Lenguaje Natural, técnicas de GLN, herramientas de GLN, Inteligencia Artificial, análisis, SimpleNLG.---ABSTRACT---In this Master's Thesis has been performed an analysis on techniques and tools for Natural Language Generation (NLG), also the Simple NLG tool has been modified in order to generate expressions in the Spanish language. This modification will allow transmitting the information to more people; around 540 million people speak Spanish. Keywords - Natural Language Generation, NLG tools, NLG techniques, Artificial Intelligence, analysis, SimpleNLG.