'Autonomous' Translation at Hand?

A number of mobile devices how have  instantaneous translation, so we have the promise of using them in any multilingual environment.   I have a Google assistant that will translate phrases.    How is this done?  Are we there yet, what more do we need?  Good review of the current tech.s.  How is the barrier been removed?

Across the Language Barrier
By Keith Kirkpatrick
Communications of the ACM, March 2020, Vol. 63 No. 3, Pages 15-17
10.1145/3379495

The greatest obstacle to international understanding is the barrier of language," wrote British scholar and author Christopher Dawson in November 1957, believing that relying on live, human translators to accurately capture and reflect a speaker's meaning, inflection, and emotion was too great of a challenge to overcome. More than 60 years later, Dawson's theory may finally be proven outdated, thanks to the development of powerful, portable real-time translation devices.

The convergence of natural language processing technology, machine learning algorithms, and powerful portable chipsets has led to the development of new devices and applications that allow real-time, two-way translation of speech and text. Language translation devices are capable of listening to an audio source in one language, translating what is being said into another language, and then translating a response back into the original language.

About the size of a small smartphone, most standalone translation devices are equipped with a microphone (or an array of microphones) to capture speakers' voices, a speaker or set of speakers to allow the device to "speak" a translation, and a screen to display text translations. Typically, audio data is captured by the microphones, processed using a natural language processing engine mated to an online language database located either in the cloud or on the device itself, and then the translation is output to the speakers or the screen. Standalone devices, with their dedicated translation engines and small portable form factors, are generally viewed as being more powerful and convenient than accessing a smartphone translation application. Further, many of these devices offer the ability to access translation databases stored locally on the device or access them in the cloud, allowing their use in areas with limited wireless connectivity.

Instead of trying to translate speech using complex rules based on syntax, grammar, and semantics, these language processing algorithms employ machine learning and statistical modeling. These initial models are trained on huge databases of parallel texts, or documents that are translated into several different languages, such as speeches to the United Nations, famous works of literature, or even multinational marketing and sales materials. The algorithms identify matching phrases across sources and measure how often and where words occur in a given phrase in both languages, which allows translators to account for differences in syntax and structure across languages. This data is then used to construct statistical models that link phrases in one language to phrases in the second, which allows for accurate and fast translation.

In practice, this means devices can translate between languages more quickly than ever before by using such modeling. Incorporating high-powered processors, quality microphones, and speakers into the device, a person can carry on a real-time, two-way conversation with someone who speaks an entirely different language. These devices represent a significant increase in accuracy and functionality above manual, text-based translation applications such as Google Translate. ... "