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Amazon Tops Overall Quarterly @OHT Survey of #NMT Engines

Amazon Tops Overall Quarterly @OHT Survey of #NMT Engines | Language Tech Market News | Scoop.it

One Hour Translation (OHT),has announced that the Amazon Web Service (AWS) Translate engine performed the best on average of the five most popular Neural Machine Translation (NMT) engines, according to the latest Q3-2018 ONEs - OHT NMT Evaluation score. ONEs is a unique human-based machine translation quality score.

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Voice Quality Framework Needed for Game Localization Industry

Kirill Soloviev on Games Localisation Conference in Warsaw: No attendees I’ve spoken to were aware of any structured framework similar to MQM (which I’ve covered extensively in my talk and workshop during Game Global Forum) that could support systematic evaluation and measurement for voice localization quality. Perhaps this is something that TAUS could undertake with help from major players like Keywords? This would enable game localizers and producers to make better decisions for their localized games from an entirely holistic view of quality across text, voice, and software aspects.

Testing player experience
One thing in common

LT-Innovate's insight:

The translation/localisation industry now has to embrace voice content in general, which raises-new quality evaluation (and technology use) questions...

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Chinese Government Language Tech Targets For AI Plan by 2020

Chinese Government Language Tech Targets For AI Plan by 2020 | Language Tech Market News | Scoop.it

By 2020, there will be a breakthrough in multilingual intelligent mutual translation. The accuracy of Chinese-English translation and English-Chinese translation will exceed 85%, and the accuracy rate of intelligent translation between ethnic minority languages ​​and Chinese would be significantly improved.

LT-Innovate's insight:

Probably the first time a government has so boldly declared a reasonable target for translation technology. But we had lots of 5-year outlooks years ago in the US and EU for translation nearing "human quality."

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Why Human Evaluation is Needed for #NLProc and #NMT Outputs

Why Human Evaluation is Needed for #NLProc and #NMT Outputs | Language Tech Market News | Scoop.it

In our latest paper (appearing at ACL 2018), The price of debiasing automatic metrics in natural language evaluation, we shed light on both these questions. The TL;DR summary is:
- existing automatic metrics are not just poor indicators of quality but are also biased (thus, at least some human evaluation is necessary) and
- the cost of debiasing these automatic metrics is about the same as conducting a full human evaluation (automatic metrics won't reduce costs, but we don't yet know what will).

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New Way to Measure Neural MT Quality?

New Way to Measure Neural MT Quality? | Language Tech Market News | Scoop.it

One Hour Translation (OHT) has recruited, trained, and tested thousands of linguists in over 50 languages, and already run well over 1,000,000 Neural MT rating and testing projects for customers. By the end of April 2018, it will publish the first human-based NMT quality index (initially covering several engines and domains and later expanding), with the goal of promoting the use of NMT across the industry.

LT-Innovate's insight:

Testing MT output may be more time & effort consuming than simply reviewing & post-editing it..

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@Lingotek Introduces New Technology Solution for Automating Linguistic Quality Evaluation

@Lingotek Introduces New Technology Solution for Automating Linguistic Quality Evaluation | Language Tech Market News | Scoop.it

Lingotek has launched new Linguistic Quality Evaluation (LQE) app that integrates quality evaluation, scoring, and reporting inside its industry-leading translation management system (TMS). The LQE app allows enterprises to create and define the core components of a best-in-class quality program.

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