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The service can be used as a dictionary by typing in words. One can translate from a book by using a scanner and an OCR like Google Drive. In its Written Words Translation function, there is a word limit on the amount of text that can be translated at once. [25]
GNMT improved on the quality of translation by applying an example-based (EBMT) machine translation method in which the system learns from millions of examples of language translation. [2] GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. [2]
Or one can include one or several example translations in the prompt before asking to translate the text in question. This is then called one-shot or few-shot learning, respectively. For example, the following prompts were used by Hendy et al. (2023) for zero-shot and one-shot translation: [35]
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
Word-sense disambiguation concerns finding a suitable translation when a word can have more than one meaning. The problem was first raised in the 1950s by Yehoshua Bar-Hillel. [33] He pointed out that without a "universal encyclopedia", a machine would never be able to distinguish between the two meanings of a word. [34]
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
With the combined power inherent in both systems, coupled with the fact that a Dictionary-Based Machine Translation works best with a "word-for-word bilingual dictionary" [3] lists of words it demonstrates the fact that a coupling of this two translation engines would generate a very powerful translation tool that is, besides being semantically ...
WP:EL#Non-English language content advises against linking to non-English content from articles in the English Wikipedia, but does not forbid it in all cases.Links to machine-translated pages from articles may lead to disputes with other editors, who may feel the quality of translation is insufficient to create a reliable source.