Language technologies in speech-enabled second language learning games : from reading to dialogue

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 237-244).Second language learning has become an important societal need over the past decades. Given that the number of language teachers is far below demand, computer-aided language learning software is becoming a promising supplement to traditional classroom learning, as well as potentially enabling new opportunities for self-learning. The use of speech technologies is especially attractive to offer students unlimited chances for speaking exercises. To create helpful and intelligent speaking exercises on a computer, it is necessary for the computer to not only recognize the acoustics, but also to understand the meaning and give appropriate responses. Nevertheless, most existing speech-enabled language learning software focuses only on speech recognition and pronunciation training. Very few have emphasized exercising the student's composition and comprehension abilities and adopting language technologies to enable free-form conversation emulating a real human tutor. This thesis investigates the critical functionalities of a computer-aided language learning system, and presents a generic framework as well as various language- and domain-independent modules to enable building complex speech-based language learning systems. Four games have been designed and implemented using the framework and the modules to demonstrate their usability and flexibility, where dynamic content creation, automatic assessment, and automatic assistance are emphasized. The four games, reading, translation, question-answering and dialogue, offer different activities with gradually increasing difficulty, and involve a wide range of language processing techniques, such as language understanding, language generation, question generation, context resolution, dialogue management and user simulation. User studies with real subjects show that the systems were well received and judged to be helpful.by Yushi Xu.Ph.D

An Intelligent Framework for Natural Language Stems Processing

This work describes an intelligent framework that enables the derivation of stems from inflected words. Word stemming is one of the most important factors affecting the performance of many language applications including parsing, syntactic analysis, speech recognition, retrieval systems, medical systems, tutoring systems, biological systems,…, and translation systems. Computational stemming is essential for dealing with some natural language processing such as Arabic Language, since Arabic is a highly inflected language. Computational stemming is an urgent necessity for dealing with Arabic natural language processing. The framework is based on logic programming that creates a program to enabling the computer to reason logically. This framework provides information on semantics of words and resolves ambiguity. It determines the position of each addition or bound morpheme and identifies whether the inflected word is a subject, object, or something else. Position identification (expression) is vital for enhancing understandability mechanisms. The proposed framework adapts bi-directional approaches. It can deduce morphemes from inflected words or it can build inflected words from stems. The proposed framework handles multi-word expressions and identification of names. The framework is based on definiteclause grammar where rules are built according to Arabic patterns (templates) using programming language prolog as predicates in first-order logic. This framework is based on using predicates in firstorder logic with object-oriented programming convention which can address problems of complexity. This complexity of natural language processing comes from the huge amount of storage required. This storage reduces the efficiency of the software system. In order to deal with this complexity, the research uses Prolog as it is based on efficient and simple proof routines. It has dynamic memory allocation of automatic garbage collection. This facility, in addition to relieve th

A Survey of Paraphrasing and Textual Entailment Methods

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.Comment: Technical Report, Natural Language Processing Group, Department of Informatics, Athens University of Economics and Business, Greece, 201

Knowledge Expansion of a Statistical Machine Translation System using Morphological Resources

Translation capability of a Phrase-Based Statistical Machine Translation (PBSMT) system mostly depends on parallel data and phrases that are not present in the training data are not correctly translated. This paper describes a method that efficiently expands the existing knowledge of a PBSMT system without adding more parallel data but using external morphological resources. A set of new phrase associations is added to translation and reordering models; each of them corresponds to a morphological variation of the source/target/both phrases of an existing association. New associations are generated using a string similarity score based on morphosyntactic information. We tested our approach on En-Fr and Fr-En translations and results showed improvements of the performance in terms of automatic scores (BLEU and Meteor) and reduction of out-of-vocabulary (OOV) words. We believe that our knowledge expansion framework is generic and could be used to add different types of information to the model.JRC.G.2-Global security and crisis managemen

A mathematics rendering model to support chat-based tutoring

Dr Math is a math tutoring service implemented on the chat application Mxit. The service allows school learners to use their mobile phones to discuss mathematicsrelated topics with human tutors. Using the broad user-base provided by Mxit, the Dr Math service has grown to consist of tens of thousands of registered school learners. The tutors on the service are all volunteers and the learners far outnumber the available tutors at any given time. School learners on the service use a shorthand language-form called microtext, to phrase their queries. Microtext is an informal form of language which consists of a variety of misspellings and symbolic representations, which emerge spontaneously as a result of the idiosyncrasies of a learner. The specific form of microtext found on the Dr Math service contains mathematical questions and example equations, pertaining to the tutoring process. Deciphering the queries, to discover their embedded mathematical content, slows down the tutoring process. This wastes time that could have been spent addressing more learner queries. The microtext language thus creates an unnecessary burden on the tutors. This study describes the development of an automated process for the translation of Dr Math microtext queries into mathematical equations. Using the design science research paradigm as a guide, three artefacts are developed. These artefacts take the form of a construct, a model and an instantiation. The construct represents the creation of new knowledge as it provides greater insight into the contents and structure of the language found on a mobile mathematics tutoring service. The construct serves as the basis for the creation of a model for the translation of microtext queries into mathematical equations, formatted for display in an electronic medium. No such technique currently exists and therefore, the model contributes new knowledge. To validate the model, an instantiation was created to serve as a proof-of-concept. The instantiation applies various concepts and techniques, such as those related to natural language processing, to the learner queries on the Dr Math service. These techniques are employed in order to translate an input microtext statement into a mathematical equation, structured by using mark-up language. The creation of the instantiation thus constitutes a knowledge contribution, as most of these techniques have never been applied to the problem of translating microtext into mathematical equations. For the automated process to have utility, it should perform on a level comparable to that of a human performing a similar translation task. To determine how closely related the results from the automated process are to those of a human, three human participants were asked to perform coding and translation tasks. The results of the human participants were compared to the results of the automated process, across a variety of metrics, including agreement, correlation, precision, recall and others. The results from the human participants served as the baseline values for comparison. The baseline results from the human participants were compared with those of the automated process. Krippendorff’s α was used to determine the level of agreement and Pearson’s correlation coefficient to determine the level of correlation between the results. The agreement between the human participants and the automated process was calculated at a level deemed satisfactory for exploratory research and the level of correlation was calculated as moderate. These values correspond with the calculations made as the human baseline. Furthermore, the automated process was able to meet or improve on all of the human baseline metrics. These results serve to validate that the automated process is able to perform the translation at a level comparable to that of a human. The automated process is available for integration into any requesting application, by means of a publicly accessible web service

Concordancing Software in Practice: An investigation of searches and translation problems across EU official languages

2011/2012The present work reports on an empirical study aimed at investigating translation problems across multiple language pairs. In particular, the analysis is aimed at developing a methodological approach to study concordance search logs taken as manifestations of translation problems and, in a wider perspective, information needs. As search logs are a relatively unexplored data type within translation process research, a controlled environment was needed in order to carry out this exploratory analysis without incurring in additional problems caused by an excessive amount of variables. The logs were collected at the European Commission and contain a large volume of searches from English into 20 EU languages that staff translators working for the EU translation services submitted to an internally available multilingual concordancer. The study attempts to (i) identify differences in the searches (i.e. problems) based on the language pairs; and (ii) group problems into types. Furthermore, the interactions between concordance users and the tool itself have been examined to provide a translation-oriented perspective on the domain of Human-Computer Interaction. The study draws on the literature on translation problems, Information Retrieval and Web search log analysis, moving from the assumption that in the perspective of concordance searching, translation problems are best interpreted as information needs for which the concordancer is chosen as a form of external support. The structure of a concordance search is examined in all its parts and is eventually broken down into two main components: the 'Search Strategy' component and the 'Problem Unit' component. The former was further analyzed using a mainly quantitative approach, whereas the latter was addressed from a more qualitative perspective. The analysis of the Problem Unit takes into account the length of the search strings as well as their content and linguistic form, each addressed with a different methodological approach. Based on the understanding of concordance searches as manifestations of translation problems, a user- centered classification of translation-oriented information needs is developed to account for as many "problem" scenarios as possible. According to the initial expectations, different languages should experience different problems. This assumption could not be verified: the 20 different language pairs considered in this study behaved consistently on many levels and, due to the specific research environment, no definite conclusions could be reached as regards the role of the language family criterion for problem identification. The analysis of the 'Problem Unit' component has highlighted automatized support for translating Named Entities as a possible area for further research in translation technology and the development of computer-based translation support tools. Finally, the study indicates (concordance) search logs as an additional data type to be used in experiments on the translation process and for triangulation purposes, while drawing attention on the concordancer as a type of translation aid to be further fine-tuned for the needs of professional translators. ***Il presente lavoro consiste in uno studio empirico sui problemi di traduzione che emergono quando si considerano diverse coppie di lingue e in particolare sviluppa una metodologia per analizzare i log di ricerche effettuate dai traduttori in un software di concordanza (concordancer) quali manifestazioni di problemi di traduzione che, visti in una prospettiva più ampia, si possono anche considerare dei "bisogni d'informazione" (information needs). I log di ricerca costituiscono una tipologia di dato ancora relativamente nuova e inesplorata nell'ambito delle ricerche sul processo di traduzione e pertanto è emersa la necessità di svolgere un'analisi di tipo esplorativo in un contesto controllato onde evitare le problematiche aggiuntive derivanti da un numero eccessivo di variabili. I log di ricerca sono stati raccolti presso la Commissione europea e contengono quantitativi ingenti di ricerche effettuate dai traduttori impiegati presso i servizi di traduzione dell'Unione europea in un concordancer multilingue disponibile come risorsa interna. L'analisi si propone di individuare le differenze nelle ricerche (e quindi nei problemi) a seconda della coppia di lingue selezionata e di raggruppare tali problemi in tipologie. Lo studio fornisce inoltre informazioni sulle modalità di interazione tra gli utenti e il software nell'ambito di un contesto traduttivo, contribuendo alla ricerca nel campo dell'interazione uomo-macchina (Human-Computer Interaction). Il presente studio trae spunto dalla letteratura sui problemi di traduzione, sull'estrazione d'informazioni (Information Retrieval) e sulle ricerche nel Web e si propone di considerare i problemi di traduzione associati all'impiego di uno strumento per le concordanze quali bisogni di informazione per i quali lo strumento di concordanze è stato scelto come forma di supporto esterna. Ogni singola ricerca è stata esaminata e scomposta in due elementi principali: la "strategia di ricerca" (Search Strategy) e l'"unità problematica" (Problem Unit) che vengono studiati rispettivamente usando approcci prevalentemente di tipo quantitativo e qualitativo. L'analisi dell'unità problematica prende in considerazione la lunghezza, il contenuto e la forma linguistica delle stringhe, analizzando ciascuna con una metodologia di lavoro appositamente studiata. Avendo interpretato le ricerche di concordanze quali manifestazioni di bisogni d'informazione, l'analisi prosegue con la definizione di una serie di categorie di bisogni d'informazione (o problemi) legati alla traduzione e incentrati sul singolo utente al fine di includere quanti più scenari di ricerca possibile. L'assunto iniziale in base al quale lingue diverse manifesterebbero problemi diversi non è stato verificato empiricamente in quanto le 20 coppie di lingue esaminate hanno mostrato comportamenti alquanto similari nei diversi livelli di analisi. Vista la peculiarità dei dati utilizzati e la specificità dell'Unione europea come contesto di ricerca, non è stato possibile ottenere conclusioni definitive in merito al ruolo delle famiglie linguistiche quali indicatori di problemi, rispetto ad altri criteri di classificazione. L'analisi dell'unità problematica ha evidenziato le entità denominate (Named Entities) quale possibile oggetto di futuri progetti di ricerca nell'ambito delle tecnologie della traduzione. Oltre a offrire un contributo per i futuri sviluppi nell'ambito dei supporti informatici alla traduzione, con il presente studio si è voluto altresì presentare i log delle ricerche (di concordanze) quale tipologia aggiuntiva di dati per lo studio del processo di traduzione e per la triangolazione dei risultati empirico-sperimentali, cercando anche di suggerire possibili tratti migliorativi dei software di concordanza sulla base dei bisogni di informazione riscontrati nei traduttori.XXV Ciclo198

Learner Modelling for Individualised Reading in a Second Language

Extensive reading is an effective language learning technique that involves fast reading of large quantities of easy and interesting second language (L2) text. However, graded readers used by beginner learners are expensive and often dull. The alternative is text written for native speakers (authentic text), which is generally too difficult for beginners. The aim of this research is to overcome this problem by developing a computer-assisted approach that enables learners of all abilities to perform effective extensive reading using freely-available text on the web. This thesis describes the research, development and evaluation of a complex software system called FERN that combines learner modelling and iCALL with narrow reading of electronic text. The system incorporates four key components: (1) automatic glossing of difficult words in texts, (2) individualised search engine for locating interesting texts of appropriate difficulty, (3) supplementary exercises for introducing key vocabulary and reviewing difficult words and (4) reliably monitoring reading and reporting progress. FERN was optimised for English speakers learning Spanish, but is easily adapted for learners of others languages. The suitability of the FERN system was evaluated through corpus analysis, machine translation analysis and a year-long study with second year university Spanish class. The machine translation analysis combined with the classroom study demonstrated that the word and phrase error rate generated in FERN is low enough to validate the use of machine translation to automatically generate glosses, but is high enough that a translation dictionary is required as a backup. The classroom study demonstrated that when aided by glosses students can read at over 100 words per minute if they know 95% of the words, whereas compared to the 98% word knowledge required for effective unaided extensive reading. A corpus analysis demonstrated that beginner learners of Spanish can do effective narrow reading of news articles using FERN after learning only 200–300 high-frequency word families, in addition to familiarity with English-Spanish cognates and proper nouns. FERN also reliably monitors reading speeds and word counts, and provides motivating progress reports, which enable teachers to set concrete reading goals that dramatically increase the quantity that students read, as demonstrated in the user study