Search results for " translatio"
showing 10 items of 503 documents
Facetten der literarischen Übersetzung
2018
Exploring translation strategies in video game localization
2012
This paper addresses the issue of video game localisation focusing on the different strategies to be used from the point of view of Translation Studies. More precisely, the article explores the possible relation between the translation approaches used in the field and the different genres or textual typologies of video games. As the narrative techniques and the story lines of video games have become more complex and well-developed, the adaptation of games entails a serious challenge for translators. Video games have evolved into multimodal and multidimensional products and new approaches and insights are required when studying the adaptation of games into different cultures. Electronic ente…
Highlight on transient activation of red/ox-dependent survival signals involving MEK/ERK and PI3/Akt signaling pathways in 27-hydroxycholesterol trea…
2014
The First translations of Machiavelli's Prince, Amsterdam - New York, Rodopi, 2010, pp. 329.
2010
Il libro analizza le prime traduzioni del Principe di Machiavelli in Europa.
Particle Swarm Optimization as a New Measure of Machine Translation Efficiency
2018
The present work proposes a new approach to measuring efficiency of evolutionary algorithm-based Machine Translation. We implement some attributes of evolutionary algorithms performing cosine similarity objective function of a Particle Swarm Optimization (PSO) algorithm then, we evaluate an English text set for translation precision into the Spanish text as a simulated benchmark, and explore the backward process. Our results show that PSO algorithm can be used for translation of multiple language sentences with one identifier only, in other words the technology presented is language-pair independent. Specifically, we indicate that our cosine similarity objective function improves the veloci…
Data Augmentation for Pipeline-Based Speech Translation
2020
International audience; Pipeline-based speech translation methods may suffer from errors found in speech recognition system output. Therefore, it is crucial that machine translation systems are trained to be robust against such noise. In this paper, we propose two methods for parallel data augmentation for pipeline-based speech translation system development. The first method utilises a speech processing workflow to introduce errors and the second method generates commonly found suffix errors using a rule-based method. We show that the methods in combination allow significantly improving speech translation quality by 1.87 BLEU points over a baseline system.
Semantic Word Error Rate for Sentence Similarity
2016
Sentence similarity measures have applications in several tasks, including: Machine Translation, Paraphrase Iden- tification, Speech Recognition, Question-answering and Text Summarization. However, measures designed for these tasks are aimed at assessing equivalence rather than resemblance, partly departing from human cognition of similarity. While this is reasonable for these activities, it hinders the applicability of sentence similarity measures to other tasks. We therefore propose a new sentence similarity measure specifically designed for resemblance evaluation, in order to cover these fields better. Experimental results are discussed.
Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation
2020
Neural machine translation systems typically are trained on curated corpora and break when faced with non-standard orthography or punctuation. Resilience to spelling mistakes and typos, however, is crucial as machine translation systems are used to translate texts of informal origins, such as chat conversations, social media posts and web pages. We propose a simple generative noise model to generate adversarial examples of ten different types. We use these to augment machine translation systems’ training data and show that, when tested on noisy data, systems trained using adversarial examples perform almost as well as when translating clean data, while baseline systems’ performance drops by…
Source-Target Mapping Model of Streaming Data Flow for Machine Translation
2017
Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building automatic translation system that facilitates processing any of various abstract entities which combine to specify underlying phonological, morphological, semantic and syntactic properties of linguistic forms and that act as the targets of linguistic rules and operations in a source language foll…
Translingual text mining for identification of language pair phenomena
2016
Translingual Text Mining (TTM) is an innovative technology of natural language processing for building multilingual parallel corpora, processing machine translation, contextual knowledge acquisition, information extraction, query profiling, language modeling, contextual word sensing, creating feature test sets and for variety of other purposes. The Keynote Lecture will discuss opportunities and challenges of this computational technology. In particular, the focus will be made on identification of language pair phenomena and their applications to building holistic language model which is a novel tool for processing machine translation, supporting professional translations, evaluation of tran…