Machine Translation

MT Quality Estimation

MT Quality Estimation (MTQE) is an AI-powered feature that provides segment-level quality estimations for machine translation (MT) suggestions. It is similar to the quality estimations for translation memory (TM) matches and non-translatables (NT).

The instant MT quality scores help guide post-editing and can be used to enhance the default (pre-translation) analysis and to assess MT engine quality.

MTQE is only available through the Memsource Translate Add-on.

Using MTQE

MTQE is only available in projects with Memsource Translate as the selected MT engine type.

MTQE does not support all language combinations. See Supported Language Pairs.

Analyses

With MTQE enabled, Default Analysis includes MT scores alongside the TM and NT scores. For example, a 75% MT score falls into the 75%-84% match range, and a 99% MT score into the 95%-99% match range. This can be turned off in Analysis options.

Pre-translation

In addition to the instant, segment-level, quality matches in the Memsource Editor, MTQE is used in pre-translation. This can be turned off in pre-translate options.

Quality Scores

Scoring categories:

  • 100% -Excellent MT match, probably no post-editing required

  • 99% - Near-perfect MT output, possibly minor post-editing required for mostly typographical errors

  • 75% - Good MT match, but likely to require some post-editing

  • No score - When there is no score, it is very likely that the MT output is of low quality. In general, it is recommended that this output not be post-edited but used for reference only.

MTQE scores appear at the segment level together with other translation resources (TM, NT, TB). Match origin is presented in a tooltip and at the bottom of the CAT panel in the metadata section.

 

Evaluating MTQE Results

Once MTQE has been enabled and employed as part of the Machine Translation process, MTQE scores for content and engine can be measured for accuracy. Direct comparison between segment-level MTQE scores and post-editing analysis is not available, but the following options provide ways to quantitatively and qualitatively evaluate MTQE scores.

Evaluating with Post-editing Analysis

Post-editing analysis indicates editing effort; how much text the Linguist or Proofreader had to edit. For post-editing analysis in projects with Machine Translation and MTQE, results are calculated as the difference between the machine translation suggestions and the final text after post-editing is finished.

In order to evaluate the results of the post-editing analysis, run a Default Analysis before the first step of the workflow to see how MT matches are categorized into MTQE bands.

When post-editing is complete, run a Post-editing Analysis with the Analyze MT option.

If the machine translation or non-translatable suggestion was accepted without any editing, the results will indicate 100%.

If the machine translation has been changed, the match rate is lower and the more the segment is changed, the lower the score will be. This is the same score-counting algorithm as the one used to calculate the score of translation memory fuzzy matches.

If the default analysis indicates a high number of quality MT matches (75% or above), the post-editing analysis reflects the correspondingly minimal to moderate amount of editing to the MT suggestions.

Evaluating the Segment Changes

To evaluate the substance of the changes made during post-editing, create a workflow that generates a report showing the changes on a segment-level.

To create this workflow, follow these steps:

  1. Create a project with two Workflow steps (e.g. pre-translation and post-editing).

  2. In the first Workflow step, pre-translate the job with only MT. This provides a snapshot of the matches to be used.

  3. In the second Workflow step, let the linguist post-edit normally.

  4. Once the workflow is completed, run the post-editing analysis to see the edit distance between the two steps (the number of changes).

  5. Select the relevant jobs, then go to Tools and select Export Workflow Changes.

    The different versions of the segments are presented.

 

MTQE Supported Language Pairs

Codes are based on ISO 639-1.

Source Target
cs de
cs en
cs hu
cs it
cs ro
da de
da en
da nb
da sv
de cs
de en
de fr
de sk
de sv
el en
en ar
en bg
en ca
en cs
en cy
en da
en de
en el
en es
en et
en fa
en fi
en fr
en he
en hi
en hr
en hu
en id
en is
en it
en ja
en ko
en lt
en lv
en ms
en nb
en nl
en pl
en pt
en ro
en ru
en sk
en sl
en sr
en sv
en th
en tr
en uk
en vi
en zh-hans
en zh-hant
es de
es en
es fr
es pt
et en
et fi
et lt
et ru
fi en
fi sv
fr de
fr en
it de
it en
it es
it fr
ja en
ja ko
ja zh-hans
ja zh-hant
ko en
lt et
lt lv
lt ru
lv en
nb da
nb en
nb sv
nl en
pl en
pt en
pt es
ru en
ru et
ru lt
ru lv
sk en
sv da
sv de
sv en
sv fi
sv nb
tr en
zh-hans en
zh-hant en
 
 
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