Search results for "Machine translation"
showing 10 items of 64 documents
Risks in neural machine translation
2020
Abstract The new paradigm of neural machine translation is leading to profound changes in the translation industry. Surprisingly good results have led to high expectations; however, there are substantial risks that have not yet been sufficiently taken into account. Risks exist on three levels: first, what kind of damage can clients and end users incur in safety-critical domains if the NMT result contains errors; second, who is liable for damage caused by the use of NMT; third, what cyber risks can the use of NMT entail, especially when free online engines are used. When establishing sustainable measures to reduce such risks, we also need to consider general principles of human behaviour if …
K-Translate - Interactive Multi-system Machine Translation
2016
The tool described in this article has been designed to help machine translation (MT) researchers to combine and evaluate various MT engine outputs through a web-based graphical user interface using syntactic analysis and language modelling. The tool supports user provided translations as well as translations from popular online MT system application program interfaces (APIs). The selection of the best translation hypothesis is done by calculating the perplexity for each hypothesis. The evaluation panel provides sentence tree graphs and chunk statistics. The result is a syntax-based multi-system translation tool that shows an improvement of BLEU scores compared to the best individual baseli…
Structural Knowledge Extraction from Mobility Data
2016
Knowledge extraction has traditionally represented one of the most interesting challenges in AI; in recent years, however, the availability of large collections of data has increased the awareness that “measuring” does not seamlessly translate into “understanding”, and that more data does not entail more knowledge. We propose here a formulation of knowledge extraction in terms of Grammatical Inference (GI), an inductive process able to select the best grammar consistent with the samples. The aim is to let models emerge from data themselves, while inference is turned into a search problem in the space of consistent grammars, induced by samples, given proper generalization operators. We will …
Towards the evaluation of automatic simultaneous speech translation from a communicative perspective
2021
In recent years, automatic speech-to-speech and speech-to-text translation has gained momentum thanks to advances in artificial intelligence, especially in the domains of speech recognition and machine translation. The quality of such applications is commonly tested with automatic metrics, such as BLEU, primarily with the goal of assessing improvements of releases or in the context of evaluation campaigns. However, little is known about how the output of such systems is perceived by end users or how they compare to human performances in similar communicative tasks. In this paper, we present the results of an experiment aimed at evaluating the quality of a real-time speech translation engine…
Why Translation Is Difficult
2017
The paper develops a definition of translation literality that is based on the syntactic and semantic similarity of the source and the target texts. We provide theoretical and empirical evidence that absolute literal translations are easy to produce. Based on a multilingual corpus of alternative translations we investigate the effects of cross-lingual syntactic and semantic distance on translation production times and find that non-literality makes from-scratch translation and post-editing difficult. We show that statistical machine translation systems encounter even more difficulties with non-literality.
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…
Natural Language Inference in Ordinary and Support Verb Constructions
2020
The family of clause types known as 'support (or 'light') verb construction' (SVC) manifests a peculiar syntax-semantics interface if compared with ordinary verb constructions (OVC). If, in e.g. She laughed, the verb licenses an argument and assigns it a semantic role, syntacticians of every stripe nowadays agree that it is the noun laugh, in She gave a laugh, which fulfils the same function. The differences between the two types have been extensively discussed in the linguistics literature (systematic research started in the 1970s), less so in Computational Linguistics. This paper has two objectives. First, it will propose an innovative type of semantic role, which is termed Cognate Semant…
Literāru tekstu mašīntulkojumu un cilvēka tulkojumu no franču un angļu valodas latviešu valodā salīdzinošā analīze
2018
Mašīntulkošanas ietekme tulkošanas jomā ir krietni pieaugusi, taču literāru tekstu tulkošanā tā tiek izmantota reti to sarežģītības dēļ. Šī maģistra darba mērķis ir salīdzināt literāru tekstu mašīntulkojumus ar cilvēka tulkojumiem un analizēt, kāda varētu būt tās iespējamā loma šajā tulkošanas apakšnozarē. Šī darba praktiskajā daļā romānu fragmentu mašīntulkojumi tika salīdzināti ar cilvēku tulkotiem tekstiem divos valodu pāros. Tekstu kvalitāte tika novērtēta, izmantojot manuālu lingvistisko, kā arī automātisko metodi. Kaut gan morfoloģiskās tipoloģijas ziņā angļu valoda un latviešu valoda ir savstarpēji attālinātākas, iegūtie rezultāti liecināja, ka sniegums bija labāks, nekā tulkojot no …
Current communication technologies in language processing
2015
Even the most cutting-edge communication-mediated technology like satellite navigation for orbit positioning, pedestrian movement recognition systems based on inertial sensors, 5G systems, let alone medical devices for coordination of human organs functionality would not be invented without technologies for language processing as an information source between humans and communication systems. Regardless of the way we communicate that is via emails, website short tweets, video conferencing systems, social networking, blogs, instant messaging through websites or mobile applications, or texting only, we use a language that is processed by computer system. Thus, the keynote paper discusses lang…
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.