Universal translator

A **universal translator** is a device that uses software to offer an instant translation of any language.

In the mid-1990s, the first commercially available speech recognition machines hit the market. They could recognize up to 40,000 words with 95% accuracy. Once the transcription of the human voice is accomplished, then each word is translated into another language via a computer dictionary. Putting the words into context, adding slang, colloquial expressions, etc. require a sophisticated understanding of the nuances of the language, leading to a field called CAT (computer assisted translation).

Nowadays speech recognition engines can work with about 99% accuracy with a little training of the user's voice, but this is still a far way off an instant translation. A speech translation system would typically integrate automatic speech recognition (ASR) using neural networks, machine translation (MT) and voice synthesis (TTS). Speech recognition has benefited from advances in deep learning and big data.

Large Language Models (LLM) — machine learning algorithms that can recognize, predict, and  generate human languages on the basis of very large text-based data sets — can improve the effectiveness and efficiency of automated question answering, machine translation, and text summarization systems, even enabling superintelligent machines.

Current applications of speech recognition:

* In-car systems - simple voice commands may be used to initiate phone calls, select radio stations or play music from a compatible smartphone, MP3 player or music-loaded flash drive.
* Health care - Front-end speech recognition is where the provider dictates into a speech-recognition engine, the recognized words are displayed as they are spoken, and the dictator is responsible for editing and signing off on the document. Back-end or deferred speech recognition is where the provider dictates into a digital dictation system, the voice is routed through a speech-recognition machine and the recognized draft document is routed along with the original voice file to the editor, where the draft is edited and report finalized.
* Therapeutic use - prolonged use of speech recognition software in conjunction with word processors has shown short-term-memory re-strengthening and cognitive benefits.
* Military - High-performance fighter aircraft - setting radio frequencies, commanding an autopilot system, setting steer-point coordinates and weapons release parameters, and controlling flight display.
* Telephony - ASR is used in contact centers by integrating it with IVR systems.
* Smartphones - the improvement of mobile processor speeds has made speech recognition practical in smartphones. Speech is used mostly as a part of a user interface, for creating predefined or custom speech commands.
* Education and daily life - for language learning, speech recognition can be useful for learning a second language. It can teach proper pronunciation, in addition to helping a person develop fluency with their speaking skills.
* Hands-free computing: Speech recognition computer user interface.
* Word processing - eliminating the need for typing enhances productivity and speeds up WPM (words per minute).
* Pronunciation evaluation in computer-aided language learning applications
* Virtual assistant (e.g. Apple's Siri)
* Babel Fish Earbuds by Google are wireless headphones that incorporate its voice assistant feature to translate 40 languages in real time.

In Star Trek, the universal translator is an "extremely sophisticated computer program" which functions by "analyzing the patterns" of an unknown foreign language, starting from a speech sample of two or more speakers in conversation. The more extensive the conversational sample, the more accurate and reliable is the "translation matrix", enabling instantaneous conversion of verbal utterances or written text between the alien language and English / Federation Standard.

On Earth, the universal translator was invented shortly before 2151, and was still experimental at the time of the launch of Enterprise NX-01. The use of a skilled linguist – in Enterprise's case, Hoshi Sato – was still required, notably in situations where reading alien languages on the displays were involved. A new language could quickly be translated in person-to-person encounters by having one speak his or her language until the universal translator gathered enough data to build a translation matrix. Sato also created the linguacode translation matrix in order to anticipate and speed up the translation of new and unknown languages.

By the 2230s, universal translators were fully incorporated directly into Starfleet communicators, directing translated audio at the recipient in the speaker's voice. They were also built into the communications systems of most starships, including shuttlecraft.

By the 24th century, universal translators had advanced to the point where a full-fledged UT could be built into the combadges worn by Starfleet personnel. It still had limitations in that it was not instantly successful with every language it encountered.