Engines

Types of engines

  • Custom

    • Using master corpora only

    • Domain-adapted (using auxiliary and/or stock corpora)

    • Stock+

  • Stock

Custom engines

All engines trained in Globalese are custom engines. There is, however, a degree to their customisation, depending on what combination of resources are used to create them.

Domain-adapted engines

Domain-adapted engines are engines containing both master and auxiliary/stock corpora, and trained using Globalese’s proprietary automated domain adaptation technology. By selecting your important in-domain TM(s) as “Master” training data, the engine will be focusing on the style and the terminology of those TM(s). You can choose to add generic stock data to extend the engine in case the volume of the in-domain data is not enough. You have also the option to add your own auxiliary data.

Use case

The typical use case for domain-adapted engines is where adhering to a particular terminology and style is important. Some examples: product documentation, end-user manuals or software documentation, where it is essential to use the right terminology and style consistently.

Required training data

The following table shows the minimum and recommended number of segments.

Includes stock corpora?

Minimum volume (segments)

Recommended volume (segments)

Includes stock corpora?

Minimum volume (segments)

Recommended volume (segments)

Yes

15,000 master

100,000+ master

No

15,000 master
200,000 total

100,000+ master
1,000,000+ total

Typical training time

The typical training time for domain-adapted engines is between 10 and 24 hours.

Stock+ engines

Stock+ engines are customised stock engines, i.e. engines trained by extending a pre-trained stock engine with you own master data. The selected master data will be part of the engine. If there is new content in the master corpora, the engine will learn it. However, you should not expect changes in terminology and style preferences in the engine based on the master data added.

Use case

The typical use case for stock+ engines is where it is important to use a generic engine trained on a large data set, which is however incorporating your own training data too. You can also use this option if you the size of your own training data is not enough to train a domain-adapted engine. Some examples: annual reports, user generated content, web pages.

Required training data

A minimum of 1,000 segments, and a maximum of 1,000,000.

Typical training time

The typical training time for stock+ engines is between 10 minutes to 4 hours.

Stock engines

You can also use pre-trained stock engines for certain language combinations.