What are the three main applications of machine translation?

Machine translation technology and products have been used in many application scenarios, such as business travel, tourism, cross-language information retrieval and so on. In terms of the object of translation, there are written language-oriented text translation and spoken language-oriented phonetic translation.

What are the types of machine translation MT systems?

There are four types of machine translation– Statistical Machine Translation (SMT), Rule-based Machine Translation (RBMT), Hybrid Machine Translation, and Neural Machine Translation.

What are use cases for Machine Translation?

Machine translation can also be used to translate PowerPoint presentations, intranet bulletins, and other similar documents. The need to translate them is often urgent. Machine translation is an excellent choice in situations where having the materials translated by a human translator would be too large an investment.

What is NMT in machine learning?

Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Why is NMT better than SMT?

NMT requires higher quality training data than SMT. Once an NMT engine has been trained, if bad data is found, the entire engine must be retrained to remove the bad data. More data can be added with an incremental training to overpower the flawed data, but this is not always practical.

How do you evaluate machine translation?

The measure of evaluation for metrics is correlation with human judgment. This is generally done at two levels, at the sentence level, where scores are calculated by the metric for a set of translated sentences, and then correlated against human judgment for the same sentences.