A variety of translation methods are being used by translators who live out there in the world. Out of those translation methods, hybrid machine translation has received a lot of attention in the recent past. Therefore, it is worth to take a look at what hybrid machine translation is and what it can offer.
What is hybrid machine translation?
Hybrid machine translation can be considered as the process, where several machine translation processes are being used inside one machine translation system to get a translation job done. It was proven that the single translation systems are not so effective. In fact, they were not in a position to provide the level of accuracy needed. As a result, there emerged the need to come up with a new and accurate translation mechanism. That’s where hybrid machine translations came into play.
When multiple machine translation methods are used, there is a possibility to overcome the issues that are linked with single translation methods. As a result, the translators are capable of ending up with a highly accurate output.
With that understanding in mind, let’s deep dive and take a look at some of the most prominent hybrid translation methodologies that are being used as of now.
The multi-engine translation approach to hybrid machine translation is associated with running multiple machine translation systems in parallel with each other. The final output is usually generated by the combined output of all the sub-systems involved in the process.
Usually, the systems that use multi engine translation methods are rule based and statistical. However, the other combinations are explored as well. A group of researchers who come from the Carnegie Mellon University were able to end up with some success when they combined transfer based, example based, statistical and knowledge based translation sub-systems into one single machine translation system.
This is one of the most widely used hybrid translation methodologies in today’s world. Depending on the working mechanism, it can provide highly effective results to the translators with getting their translation work done. If you are a translator, you are encouraged to take a look at the very first thing, while you are deep diving into the hybrid translation methodologies.
Statistical rule generation
Secondly, you must take a look at the statistical rule generation. In this hybrid translation approach, statistical data is being used in order to generate syntactic and lexical rules. The input will then be processed along with the assistance of these rules. The functionality is pretty much similar to a rule based translator.
This approach has the ability to avoid the time consuming and complex tasks of creating a set of fine-grained and comprehensive linguistic rules and extracting those rules via a training corpus. This approach still has many issues. If you are about to try it, you are encouraged to have a basic understanding of these issues as well.
In fact, most of the issues that the statistical rule generation hybrid translation method has been inherent from the basic principles that create it. For example, the accuracy of the translation heavily depends on the similarities that exist in between the text contained in the training corpus and the input text. Due to the same reason, the statistical rule generation hybrid translation method was able to achieve a high level of success in some of the domain-specific applications. On the other hand, it is not good in providing perfect results in a few other applications.
Multi pass can also be considered as a popular hybrid translation approach that you can find out there in the world. In this approach, the input is being processed serially for multiple times. Out of the techniques that are used in multi-pass translation, the most common technique is to pre-process the inputs along with the assistance of a rule based machine translation system.
The output that comes from a rule based preprocessor is then being passed into the statistical machine translating system. This system is capable of providing a translator with the final translated output.
The multi pass translation technique is widely being used in order to limit the extent of information that a statistical system should consider. This will significantly reduce the processing power needed as well. On the other hand, it removes the need to have a rule based system in order to complete a translation for getting a document translated from one language to another. On the other hand, this translation approach is in a position to significantly reduce the human labor and effort that is needed to develop a system.
Apart from these hybrid translation approaches, many other approaches are being used and tested. However, these three approaches hold a prominent place out of those approaches.