What does machine translation primarily do?

Machine translation primarily focuses on translating text or speech from one language to another, facilitating communication across different linguistic backgrounds. This technology is designed to break down language barriers by providing accurate and efficient translations, enabling users to understand content in a language they may not be proficient in. It employs various techniques, including neural networks and linguistic algorithms, to ensure that the meaning and context of the original language are preserved as closely as possible in the translated content.

The other options describe different functionalities that are not inherent to machine translation. Summarizing documents, for instance, involves condensing lengthy texts into shorter versions while retaining essential information. Extracting key phrases refers to identifying and isolating significant terms within a text, often used for indexing or information retrieval purposes. Analyzing sentiment involves assessing and interpreting emotional tones or opinions expressed in text data, such as customer feedback, rather than translating languages. Each of these processes serves distinct purposes within the realm of natural language processing, separate from the core function of machine translation.