What is Real-Time Machine Translation?


Real-time machine translation refers to the process of a computer reproducing the reasoning characteristic of the human mind that allows for simultaneous real-time translation. Translation is based on interpreting the meaning of language or an action, and it takes a lot of work for our brains to conduct this analysis and consider the nuances of the specific situation. While computers have not yet mastered this activity, developments in real-time machine translation are bringing us closer to smarter, reactive, and more culturally aware devices. Currently, real-time machine translation is useful for quickly translating a written work into another language and deriving a general notion of text or audio. Systems have been designed that listen to student speech, and coach (or rate) a student’s speech for pacing, tone, dialect, and accuracy of pronunciation. Statistical machine translation is a sub-field that explores the use statistical methods to instantly interpret one language and translate it into another. (Google Translate uses this approach.) The low cost of and ease with which these services can be embedded in websites has made them very popular. In the next generation of machine translation, machines will be able to understand and interpret the personality behind speech, text, and gestures. Ray Kurzweil, a major thought leader in the area of machine translation, believes that before 2030, machines will reach a sufficient level of understanding of human written and spoken communications to allow for seamless and highly accurate translation. While not at that level today, the state of machine learning has advanced considerably in the past few years, and now has a great many applications in learning, teaching, and global communications.

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