Document Translation for Cross-Language Text Retrieval at the University of Maryland

The University of Maryland participated in three TREC-6 tasks: ad hoc retrieval, cross-language retrieval, and spoken document retrieval. The principal focus of the work was evaluation of a cross-language text retrieval technique based on fully automatic machine translation. The results show that approaches based on document translation can be approximately as effective as approaches based on query translation, but that additional work will be needed to develop a solid basis for choosing between the two in specific applications. Ad hoc and spoken document retrieval results are also presented

Real-Time Statistical Speech Translation

This research investigates the Statistical Machine Translation approaches to translate speech in real time automatically. Such systems can be used in a pipeline with speech recognition and synthesis software in order to produce a real-time voice communication system between foreigners. We obtained three main data sets from spoken proceedings that represent three different types of human speech. TED, Europarl, and OPUS parallel text corpora were used as the basis for training of language models, for developmental tuning and testing of the translation system. We also conducted experiments involving part of speech tagging, compound splitting, linear language model interpolation, TrueCasing and morphosyntactic analysis. We evaluated the effects of variety of data preparations on the translation results using the BLEU, NIST, METEOR and TER metrics and tried to give answer which metric is most suitable for PL-EN language pair.Comment: machine translation, polish englis

MATREX: DCU machine translation system for IWSLT 2006

In this paper, we give a description of the machine translation system developed at DCU that was used for our first participation in the evaluation campaign of the International Workshop on Spoken Language Translation (2006). This system combines two types of approaches. First, we use an EBMT approach to collect aligned chunks based on two steps: deterministic chunking of both sides and chunk alignment. We use several chunking and alignment strategies. We also extract SMT-style aligned phrases, and the two types of resources are combined. We participated in the Open Data Track for the following translation directions: Arabic-English and Italian-English, for which we translated both the single-best ASR hypotheses and the text input. We report the results of the system for the provided evaluation sets

Developing Deployable Spoken Language Translation Systems given Limited Resources

Approaches are presented that support the deployment of spoken language translation systems. Newly developed methods allow low cost portability to new language pairs. Proposed translation model pruning techniques achieve a high translation performance even in low memory situations. The named entity and specialty vocabulary coverage, particularly on small and mobile devices, is targeted to an individual user by translation model personalization

Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation

Prior work on Sign Language Translation has shown that having a mid-level sign gloss representation (effectively recognizing the individual signs) improves the translation performance drastically. In fact, the current state-of-the-art in translation requires gloss level tokenization in order to work. We introduce a novel transformer based architecture that jointly learns Continuous Sign Language Recognition and Translation while being trainable in an end-to-end manner. This is achieved by using a Connectionist Temporal Classification (CTC) loss to bind the recognition and translation problems into a single unified architecture. This joint approach does not require any ground-truth timing information, simultaneously solving two co-dependant sequence-to-sequence learning problems and leads to significant performance gains. We evaluate the recognition and translation performances of our approaches on the challenging RWTH-PHOENIX-Weather-2014T (PHOENIX14T) dataset. We report state-of-the-art sign language recognition and translation results achieved by our Sign Language Transformers. Our translation networks outperform both sign video to spoken language and gloss to spoken language translation models, in some cases more than doubling the performance (9.58 vs. 21.80 BLEU-4 Score). We also share new baseline translation results using transformer networks for several other text-to-text sign language translation tasks

Translating bus information into sign language for deaf people

This paper describes the application of language translation technologies for generating bus information in Spanish Sign Language (LSE: Lengua de Signos Española). In this work, two main systems have been developed: the first for translating text messages from information panels and the second for translating spoken Spanish into natural conversations at the information point of the bus company. Both systems are made up of a natural language translator (for converting a word sentence into a sequence of LSE signs), and a 3D avatar animation module (for playing back the signs). For the natural language translator, two technological approaches have been analyzed and integrated: an example-based strategy and a statistical translator. When translating spoken utterances, it is also necessary to incorporate a speech recognizer for decoding the spoken utterance into a word sequence, prior to the language translation module. This paper includes a detailed description of the field evaluation carried out in this domain. This evaluation has been carried out at the customer information office in Madrid involving both real bus company employees and deaf people. The evaluation includes objective measurements from the system and information from questionnaires. In the field evaluation, the whole translation presents an SER (Sign Error Rate) of less than 10% and a BLEU greater than 90%

Introduction : literary texts and their translations as an object of research

This special issue of the International Journal of Literary Linguistics offers seven state-of-the-art contributions on the current linguistic study of literary translation. Although the articles are based on similar data – literary source texts and their translations – they focus on diverse aspects of literary translation, study a range of linguistic phenomena and utilize different methodologies. In other words, it is an important goal of this special issue to illuminate the current diversity of possible approaches in the linguistic study of translated literary texts within the discipline of translation studies. At the same time, new theoretical and empirical insights are opened to the study of the linguistic phenomena chosen by the authors of the articles and their representation or use in literary texts and translations. The analyzed features range from neologisms to the category of passive and from spoken language features to the representation of speech and multilingualism in writing. Therefore, the articles in this issue are not only relevant for the study of literary translation or translation theory in general, but also for the disciplines of linguistics and literary studies – or most importantly, for the cross-disciplinary co-operation between these three fields of study. The common theme that all these articles share is how the translation process shapes, transfers and changes the linguistic properties of literary texts as compared to their sources texts, other translations or non-translated literary texts in the same language and how this question can be approached in research. All articles provide new information about the forces that direct and affect translators’ textual choices and the previously formulated hypotheses about the functioning of such forces. The articles illustrate how translators may perform differently from authors and how translators’ and authors’ norms may diverge at different times and in different cultures. The question of how translation affects the linguistic properties of literary translations is approached from the viewpoint of previously proposed claims or hypotheses about translation. In the following, we will introduce these viewpoints for readers who are not familiar with the recent developments in translation studies. At the same time, we will shortly present the articles in this issue