BLEU allows researchers to assign numerical scores measuring the overlap between pairs of sentences, and Meta says its model produces an improvement of 44 percent in BLEU scores across supported languages . However, as is often the case in AI research, judging progress based on benchmarks requires context.progress of different machine translation models, they do not offer anRemember: Meta’s dataset consists of 3001 sentences, and each has been translated only by a single individual.
Fan said that BLEU scores had also been complemented with human evaluation, and that this feedback was very positive, and also produced some surprising reactions. : they don’t want the tools needed to preserve their language in anyone’s hands but their own. For others, the issues are less existential, but more concerned with questions of quality and influence.Meta’s engineers explored some of these questions by conducting interviews with 44 speakers of low-resource languages. These interviewees raised a number of positive and negative affects of opening up their languages to machine translation.
If it is the same tool as what Facebook uses in translating Indian languages to English and vice versa, then don't bother looking at it.
So cool! Our company is stepping into the NFT and metaverse space. See you there!
should i even learn another language?
So, after translating where Meta’s tool is sending the data to 😎😆