Machine translation converts text from one human language to another. As an NLP application, it is challenging because languages have different grammatical rules; deep-learning-based solutions are generally considered a good fit. section 7.3
Machine translation
Machine translation is the automated conversion of text or speech from one human language to another.
How Data Without Labels covers it
- How deep it goes
- Explains grammatical differences as a challenge and names deep learning as a good fit, but gives no translation-specific implementation.
- How it connects
- Links machine translation to natural language processing, text data, and deep learning.
Also explained in
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Inside AIAutomatic translation is the computational conversion of content from one human language to another.
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Starting Data Analytics with Generative AI and PythonCode conversion is the transformation of source code from one programming language into equivalent code in another language.
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Learn Generative AI with PyTorchThe task of automatically translating text from one natural language to another.
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How Large Language Models WorkMachine translation is the automated conversion of text or speech from one human language into another by computational systems.
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Data Analysis with LLMsTranslation is the conversion of content from a source language into an equivalent target language.
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Introduction to Generative AI, Second EditionMachine translation is the automated conversion of text or speech from one human language into another.
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Microsoft Azure in ActionMachine translation is the automated conversion of text or speech from one natural language into another.
Compare how 8 books explain machine translation →
Related concepts
- BLEU scoremeasured by · BLEU is an automatic text-generation evaluation metric that compares candidate text with reference text using modified n-gram precision and a brevity penalty.
- language modelused by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
- encoderuses · An encoder is a component that transforms input data into an encoded representation for subsequent processing, reconstruction, comparison, or transmission.
- n-gram modelused by · An n-gram model is a probabilistic language model that estimates sequence probabilities using contiguous sequences of a fixed number of tokens, typically to predict a token from preceding context.
- text-to-speech conversionuses · Text-to-speech conversion is the computational synthesis of spoken audio from written text.
This explainer was generated by Manning's knowledge graph from the text of Data Without Labels. The section links point to the parts of the book it draws on.