Articles

This paper presents initial experiments in data-driven morphological analy- sis for Finnish using deep learning methods. Our system uses a character based bidirectional LSTM and pretrained word embeddings to predict a set of morpho- logical analyses for an input word form. We present experiments on morpholog- ical analysis for Finnish. …...

AbstractThanks to the great progress seen in the machine translation (MT) field in recent years, the use and perception of MT by translators need to be revisited. The main objective of this paper is to determine the perception, productivity and the postediting effort (in terms of time and number of …...

AbstractWhile MT+PE has become an industry standard, our translation schools are not able to accompany these changes by updating their academic programs. We polled 100 pre-professionals to confirm that in our local context they are reluctant to accept post-editing jobs mainly because they have inherited pre-conceptions or negative opinions about …...

AbstractWe will present our solution to replace the usage of publicly available machine translation (MT) services in companies where privacy and confidentiality are key. Our MT portal can translate across a variety of languages using neural machine translation, and supports an extensive number of file types. Corporations are using it …...

AbstractI will try to answer the question of whether Machine Translation (MT) can be considered a full translation process. I argue that, instead, it should be seen as part of a process performed by translators, in which MT plays a fundamental support role. The roles of translators and MT in …...

AbstractOver the last 4 years, Infor has been implementing machine translation (MT) in its translation process. In this paper, the results of both statistical and neural MT projects are provide to give an insight in the advantages and disadvantages of MT use in a large company. We also offer a …...

AbstractWhile Neural Machine Translation (NMT) technology has been around for a few years now in research and development, it is still in its infancy when it comes to customization readiness and experience with implementation on an enterprise scale with Language Service Providers (LSPs). For large, multi-language LSPs, it is therefore …...

AbstractWith the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language models to understand human intent. Since these models require large amounts of data and in-domain knowledge, expanding an equivalent service into new markets is disrupted by …...

AbstractIn this paper, we present the challenge entailed by implementing a mobile version of a neural machine translation system, where the goal is to maximise translation quality while minimising model size. We explain the whole process of implementing the translation engine on an English–Spanish example and we describe all the …...

AbstractMachine Translation (MT) already plays an important part in software development process at McAfee where the technology can be leveraged to provide early builds for localization and internationalization testing teams. Behavior Driven Development (BDD) has been growing in usage as a development methodology in McAfee. Within BDD, the Gherkin Controlled …...

AbstractTelugu is the fifteenth most commonly spoken language in the world with an estimated reach of 75 million people in the Indian subcontinent. At the same time, it is a severely low resourced language. In this paper, we present work on English–Telugu general domain machine translation (MT) systems using small …...

AbstractWe present an approach to neural machine translation (NMT) that supports multiple domains in a single model and allows switching between the domains when translating. The core idea is to treat text domainsasdistinctlanguagesandusemultilingual NMT methods to create multi-domain translation systems; we show that this approach results in significant translation quality …...

AbstractWe test a series of techniques to predict punctuation and its effect on machine translation (MT) quality. Several techniques for punctuation prediction are compared: language modeling techniques, such as n-grams and long shortterm memories (LSTM), sequence labeling LSTMs (unidirectional and bidirectional), and monolingual phrase-based, hierarchical and neural MT. For actual …...

AbstractA prerequisite for training corpus-based machine translation (MT) systems – either Statistical MT (SMT) or Neural MT (NMT) – is the availability of high-quality parallel data. This is arguably more important today than ever before, as NMT has been shown in many studies to outperform SMT, but mostly when large …...

AbstractThis paper presents a case study in translating short image captions of the Visual Genome dataset from English into Hindi using out-of-domain data sets of varying size. We experiment with three NMT models: the shallow and deep sequence-tosequence and the Transformer model as implemented in Marian toolkit. Phrase-based Moses serves …...

AbstractNeural Machine Translation (NMT) systems require a lot of data to be competitive. For this reason, data selection techniques are used only for finetuning systems that have been trained with larger amounts of data. In this work we aim to use Feature Decay Algorithms (FDA) data selection techniques not only …...

AbstractNeural Machine Translation (NMT) has achieved promising results comparable with Phrase-Based Statistical Machine Translation (PBSMT). However, to train a neural translation engine, much more powerful machines are required than those required to develop translation engines based on PBSMT. One solution to reduce the training cost of NMT systems is the …...

AbstractThis paper presents the preliminary results of an ongoing academia-industry collaboration that aims to integrate MT into the workflow of Swiss Post’s Language Service. We describe the evaluations carried out to select an MT tool (commercial or open-source) and assess the suitability of machine translation for post-editing in Swiss Post’s …...

AbstractWhile systems using the Neural Network-based Machine Translation (NMT) paradigm achieve the highest scores on recent shared tasks, phrase-based (PBMT) systems, rule-based (RBMT) systems and other systems may get better results for individual examples. Therefore, combined systems should achieve the best results for MT, particularly if the system combination method …...

AbstractThis study analyzes usage statistics and the results of an end-user survey to compile a snapshot of the current use and users of one online machine translation (MT) tool, Multilizer’s PDF Translator1. The results reveal that the tool is used predominantly for assimilation purposes and that respondents use MT often. …...