linerafrica.blogg.se - Editing machine transcriptions

Editing machine transcriptions full#
Editing machine transcriptions software#

Human translations can be more prone to errors when translating numerical values and to making omissions. Some MT engines also perform very poorly with terminology. However, machine translations also tend to produce more awkward-sounding phrases. Machine engines are also less prone to leaving content out (e.g., omitting a clause within a long legal paragraph). For example, machine translations tend to be more accurate when transposing numerical values. In general, the types of errors found in human translations differ greatly from those found in machine-translated text.

Taking a look at what the TM offers, the post-editor can either use these previous translation segments in their entirety or make the necessary adjustments.Ĭompared to reviewing human translations, editing machine-generated translations requires a very different approach and set of skills.

Editing machine transcriptions full#

These previously translated segments contained in the TM, may be either a fuzzy (an approximation) or a full match of the current source segment.

If the MT output is of poor quality, they delete whatever the MT is offering and re-translate it from scratch (as in the translation process listed above).Īs part of a machine-translation post-editing process, the project will often include a translation memory (TM) that contains translation segments from previous translation jobs of similar/related material, usually from clients or other similar projects.

If the MT output is acceptable, they continue working to improve the text.

The post-editor makes an in-the-moment judgment of the MT output’s quality, based on linguistic knowledge and explicit instructions.

The MT output is compared to the source text.

First, the post-editor (linguist) reads a sentence, or segment, of the MT output (that is, the process begins at the target).

In post-editing machine translated content, however, the process is very different, and it is generally performed with the use of a computer-assisted translation tool (CATT):

Editing machine transcriptions software#

And finally, type their version in the target language (translation) in a software program or interface.ĭepending on the content and project, the translator may edit the text immediately, conduct additional research, or return to it later when the entire text has been translated.Formulate the translation internally (i.e., in their brain).When translating content from scratch, faced with a “target” (the would-be translation) that is a blank canvas, translators normally: This training begins with the mental process used when reviewing bilingual content. Quite recently, academia has started developing curricula to address the growing demand for human post-editors. Not all translators are comfortable doing post-editing even if they sign on for post-editing, they often require training.

The processes of translating and post-editing machine-generated content are quite different each one calls for distinct skills and training. With the right technology tools in place, the post-editing process will improve the output quality of a current translation project, allow you to store that quality data in your translation memory (TM), and also improve the efficiency and accuracy of the machine translation engine for future projects. Our skilled post-editors rely on their experience with machine or automated translation output not only to provide corrections, but also to improve future output. Moreover, if you are using a Custom Neural Machine Translation Engine (CMTE), feedback from a human linguist is necessary for retraining purposes to improve performance.Īt Trusted Translations, we have expert linguists trained specifically to post-edit machine-generated translations. In most cases, to guarantee a highly reliable translation output when utilizing machine translation, human post-editing is indispensable. The accuracy and effectiveness of machine translations will depend on numerous factors, such as language combination, content domain, complexity and technical level, whether the content is prosaic or creative, how well-written the source content is, input format, and more.ĭue to these infinite variations, machine translations are not able to detect every linguistic nuance and produce a correct translation in every instance. Have machine translations reached full parity with humans? Not quite-which makes a human touch essential. Human Post-Editing of Machine Translations.