Machine translation quality has improved remarkably over the years. Automatic translations are becoming more and more usable in different contexts. Heavy users might have noticed that the development, Cependant, hasn’t been linear. Machine translation has moved up some kind of quality steps.
The reason for jumps to higher quality steps is technical. Machine translation technologies are getting much attention and resources. The idea of how machine translation works has changed. The steps from rule-based to statistical machine translation and then to the use of artificial intelligence (or AI) have all improved the quality. The technologies are getting closer to the way humans adapt their first languages.
Les petits bébés apprennent une langue en étant entouré dans leur vie quotidienne. Ils entendent encore et encore. Ils essaient de dire un mot ou deux. Ils vont d'abord dire mal, mais d'améliorer en répétant plusieurs fois. Ils apprennent de nouveaux mots et ce que ces mots signifient. Ils le font même sans avoir quelqu'un expliquer explicitement ces choses pour les. Ils entendent, leur cerveau travaillent très dur et ils apprennent.
L'utilisation d'un grand nombre de données
AI et les réseaux de neurones apprennent les langues un peu comme des bébés. Les données sont l'élément le plus important de. pour les technologies, il est essentiel de disposer de données assez. Tout comme pour les bébés, il est essentiel d'entendre les gens parler et lire à voix haute. Plus est mieux. Il y a beaucoup de parents, en disant de recherche devraient lire à leurs enfants. Lorsque les parents lisent à leurs enfants, ils réussiront dans la vie. They will have better skills in communication and linguistic. No human nor machine can learn without enough data coming in.
Using good quality data
De même, the quality of the data is important. One-sided interactions with the language limit the learning process. Varied and rich exposure to different uses of language brings more versatile results. Mais, too wide data isn’t going to work either. There should be enough repetition to ensure remembering. Babies learn first those words which they hear most often. They hear them in different sentences and situations. The more they hear those words the stronger the meaning and usage of them become in their minds.
Getting support for the learning
All language learners need some outside support as well. Control by someone who knows more. Parents tend to correct if a child says something in the wrong way. Or at least they repeat the idea in other words back to the child. They often use phrases like ’did you mean that’ or ’what do you try to say’ or ’did I understand you correctly’. Even the most modern technologies need that kind of guidance and feedback as well.
The difference is that AI won’t really understand. Technologies know words and can link meanings and synonyms. They can produce spoken or written texts. They can even maintain a conversation through chat or customer service. But they don’t understand. Babies and children can. Human brains are just amazing. We are clever enough to use machines and technologies in those tasks that can be outsourced. This way we can concentrate on more interesting and creative tasks, and challenge our brains to keep on improving.
(Final note: AI and neural nets are very advanced technologies. For many they are just abstract and unclear terms. This text simplifies them and tries to give an overall idea of how they work. If you want to tell your own description, we’ll be more than happy to publish it here on our blog. Just leave a comment below or email us.)