BILINGUALISM AND THE MAINTENANCE OF THE MOTHER TONGUE IN MULTILINGUAL SINGAPORE

Two issues have been identified that act against the development of a strong bilingual and biliteracy proficiency among pupils in Singapore schools: 1. English is perceived as having a much higher status than the Mother Tongue (MT) and the language in which success is primarily measured given its primacy as the language of instruction in all subjects except the MT. Consequently, children’s use of their MT has been observed to decline in favour of English; 2. English and the MT are taught in effect as a form of double monolingualism, in watertight compartments, with no opportunity for bilingual learning or reflection in class on the relationship between the two languages. This artificially blocks pupils’ access to the other language and prevents the development of a more robust bilingual. In this presentation, I will describe the ways in which the MT is maintained in Singapore, and in particular focus on the research that has recently been completed on the use of dual language books to rejuvenate the interest and ability to read in Malay in bilingual Malay children

Cross-Lingual Adaptation using Structural Correspondence Learning

Cross-lingual adaptation, a special case of domain adaptation, refers to the transfer of classification knowledge between two languages. In this article we describe an extension of Structural Correspondence Learning (SCL), a recently proposed algorithm for domain adaptation, for cross-lingual adaptation. The proposed method uses unlabeled documents from both languages, along with a word translation oracle, to induce cross-lingual feature correspondences. From these correspondences a cross-lingual representation is created that enables the transfer of classification knowledge from the source to the target language. The main advantages of this approach over other approaches are its resource efficiency and task specificity. We conduct experiments in the area of cross-language topic and sentiment classification involving English as source language and German, French, and Japanese as target languages. The results show a significant improvement of the proposed method over a machine translation baseline, reducing the relative error due to cross-lingual adaptation by an average of 30% (topic classification) and 59% (sentiment classification). We further report on empirical analyses that reveal insights into the use of unlabeled data, the sensitivity with respect to important hyperparameters, and the nature of the induced cross-lingual correspondences

Building a sign language corpus for use in machine translation

In recent years data-driven methods of machine translation (MT) have overtaken rule-based approaches as the predominant means of automatically translating between languages. A pre-requisite for such an approach is a parallel corpus of the source and target languages. Technological developments in sign language (SL) capturing, analysis and processing tools now mean that SL corpora are becoming increasingly available. With transcription and language analysis tools being mainly designed and used for linguistic purposes, we describe the process of creating a multimedia parallel corpus specifically for the purposes of English to Irish Sign Language (ISL) MT. As part of our larger project on localisation, our research is focussed on developing assistive technology for patients with limited English in the domain of healthcare. Focussing on the first point of contact a patient has with a GP’s office, the medical secretary, we sought to develop a corpus from the dialogue between the two parties when scheduling an appointment. Throughout the development process we have created one parallel corpus in six different modalities from this initial dialogue. In this paper we discuss the multi-stage process of the development of this parallel corpus as individual and interdependent entities, both for our own MT purposes and their usefulness in the wider MT and SL research domains

Marketing and Advertising Translation: Humans vs Machines in the field of cosmetics

This undergraduate thesis focuses on a very specific field of specialized translation: advertising and marketing translation. Indeed, the high degree of specialization involved in this activity provides a testing ground for a reconsideration of the importance of the human translator and a reformulation of their role. The constant development of new technologies creates ever more sophisticated translation programs, which in turn revives the long-standing machine vs human translation debate. The aim of this project is to conduct a practical exercise targeted at verifying whether specialization in translation always requires the supervision of humans equipped with the relevant linguistic knowledge and technical background, or whether, on the contrary, machine translation can at present provide valid enough results and a sufficient level of reliability.El presente Trabajo de Fin de Grado se centra en un campo muy concreto de la traducción especializada: la traducción para la publicidad y la mercadotecnia. De hecho, el alto grado de especialización que implica esta actividad proporciona un campo de pruebas para una reconsideración de la importancia del traductor humano y una reformulación de su papel. El desarrollo creciente e ininterrumpido de las nuevas tecnologías está produciendo programas de traducción cada vez más sofisticados, lo que a su vez reaviva el viejo debate que confronta la traducción humana y la traducción automática. El objetivo de este proyecto es llevar a cabo un ejercicio práctico destinado a verificar si la especialización en la traducción siempre requiere la supervisión de personas con la formación lingüística y los conocimientos técnicos pertinentes, o si, por el contrario, la traducción automática puede en la actualidad proporcionar por si sola resultados suficientes y un nivel suficiente de fiabilidad.Grado en Estudios Inglese

Comparison of SYSTRAN and Google Translate for English→ Portuguese

Two machine translation (MT) systems, a statistical MT (SMT) system and a hybrid system (rule-based and SMT) were tested in order to compare various MT performances. The source language was English (EN) and the target language Portuguese (PT). The SMT tool gave much fewer errors than the hybrid system. Major problem areas of both systems concerned the transfer of verb systems from source to target language, and of the hybrid system the word-to-word translation, since its resources are mainly dictionaries and not corpora.Dos sistemes de traducció automàtica (MT), un sistema estadístic (SMT) i un sistema híbrid (sistema basat en regles i SMT) es van posar a prova per tal de comparar divereses resultats en MT. La llengua d'orígen era l'anglès (EN) i a llengua de destí el portuguès (PT). L'eina SMT va donar força menys errors que el sistema híbrid. La major part dels problemes d'ambdes eines se centraven en el sistema de transferència del verb de la llengua origen a la llengua destí, i en el cas del sistema híbrid en la traducció paraula a paraula, ja que els seus recursos són sobretot diccionaris i no pas corpus.Se pusieron a prueba dos sistemas de traducción automática (MT), uno de de ellos estadístico (SMT) y el otro híbrido (basado en reglas y SMT) a fin de comparar diversos resultados en MT. La lengua de origen era el inglés (EN) y la lengua de destino el portugués (PT). La herramienta SMT generó bastantes menos errores que el sistema híbrido. La mayor parte de los problemas de ambos instrumentos se centraron en el método de transferencia del verbo de la lengua origen a la lengua destino, y en el caso del sistema híbrido, en la traducción palabra a palabra, ya que sus recursos son sobre todo diccionarios y no corpus

Natural Language Processing at the School of Information Studies for Africa

The lack of persons trained in computational linguistic methods is a severe obstacle to making the Internet and computers accessible to people all over the world in their own languages. The paper discusses the experiences of designing and teaching an introductory course in Natural Language Processing to graduate computer science students at Addis Ababa University, Ethiopia, in order to initiate the education of computational linguists in the Horn of Africa region

Natural language processing and advanced information management

Integrating diverse information sources and application software in a principled and general manner will require a very capable advanced information management (AIM) system. In particular, such a system will need a comprehensive addressing scheme to locate the material in its docuverse. It will also need a natural language processing (NLP) system of great sophistication. It seems that the NLP system must serve three functions. First, it provides an natural language interface (NLI) for the users. Second, it serves as the core component that understands and makes use of the real-world interpretations (RWIs) contained in the docuverse. Third, it enables the reasoning specialists (RSs) to arrive at conclusions that can be transformed into procedures that will satisfy the users' requests. The best candidate for an intelligent agent that can satisfactorily make use of RSs and transform documents (TDs) appears to be an object oriented data base (OODB). OODBs have, apparently, an inherent capacity to use the large numbers of RSs and TDs that will be required by an AIM system and an inherent capacity to use them in an effective way