Search results for "neural machine translation"

showing 3 items of 3 documents

Latviešu–angļu mašīntulkošanas optimizācija

2018

Pēdējo gadu laikā notikusī straujā dziļās mašīnmācīšanās attīstība ir ļāvusi attīstīties arī mašīntulkošanas nozarei. Lai palīdzētu uzņēmējiem apgūt starptautiskos tirgus un ļautu datortehnikas lietotājiem izmantot tehnoloģijas dzimtajā valodā, ir svarīgi attīstīt latviešu valodas mašīntulkošanas tehnoloģijas. Šajā darbā aprakstīti neirontulkošanas darbības principi un latviešu valodas morfoloģiskās īpatnības. Identificētas metodes, kas pašlaik sniedz labākos rezultātus latviešu valodas tulkošanā. Papildus tam ir veikti eksperimenti ar neirontulkošanas sistēmu trenēšanu un optimizāciju latviešu valodas tulkošanai. Darbā tiek aprakstīts jauns latviešu valodas vārdu segmentācijas algoritms, k…

neirontulkošanamašīntulkošanaDatorzinātnelatviešu valodas apstrādeneural machine translationneironu tīkli
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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.

Machine translationComputer sciencePipeline (computing)media_common.quotation_subjectSpeech recognition[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]speech translationSpeech processingcomputer.software_genreneural machine translation[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]robustness to errorsWorkflow[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]Speech translationQuality (business)Noise (video)Suffixcomputermedia_commonHuman Language Technologies – The Baltic Perspective - Proceedings of the Ninth International Conference Baltic HLT 2020
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Machine Translation and Gender biases in video game localisation: a corpus-based analysis

2021

The video game industry has been a historically gender-biased terrain due to a higher number of male protagonists and hypersexualised representations [Dietz, 1998; Downs & Smith, 2010; Lynch et al., 2016]. Nowadays, echoing the debate on inclusive language, companies attempt to erase gender disparity by introducing main female characters as well as non-binary characters. From a technological point of view, even though recent studies show that Machine Translation remains largely unadopted by individual video game localisers [Rivas Ginel, 2021], multilanguage vendors are willing to invest in these tools to reduce costs [LIND, 2020]. However, the predominance of the masculine in Natural La…

gender biasGender biasesNeural Machine Translation NMTNMTcorpusvideo gamescorpora[SHS.LANGUE]Humanities and Social Sciences/LinguisticsVideo game Localisation[SHS.LANGUE] Humanities and Social Sciences/LinguisticsComputingMilieux_MISCELLANEOUSmachine translation
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