Reacción a "Meta designs artificial intelligence model capable of instant speech-to-speech translation"

Machine translation has evolved from rule-based systems and statistical calculations to today's large linguistic models or LLMs, thanks to the computational power available. Within this context, the publication presents a breakthrough in faster, more reliable and universal translation systems. It highlights the ability to perform speech-to-speech translations directly, without intermediate steps (speech-to-text, text-to-text, text-to-speech translation), speeding up the process. In addition, it supports multiple languages, bringing us ever closer to the utopia of a universal automatic translator. It is also interesting to note how the improvements discussed in the publication are not based on a greater number of parameters of the model to be trained, but on a more intelligent preprocessing of the available information, even incorporating new sources of additional information to improve translations.

So far, most machine translators translate from language X to Y using English as an intermediary. However, this publication proposes direct translations from language X to language Y, thus eliminating accumulated errors. This is achieved through the use of a common representation space where sentences with similar meanings are close together, regardless of language. However, the training used is still largely based on translations from or into English. Moreover, all the tests and trials shown in the main text of the publication have been carried out between language X and English, or vice versa. It will then be necessary to review the supplementary material in the publication and to test the proposed system once available between language pairs that do not include English or some other major language, which remains a challenge. Finally, it should be noted that, although the speech-to-speech translation is performed correctly, it does not take into account vocal inflections and other emotional components that may affect the accuracy of the final translation.