At the end of the 19th century, L. L. Zamenhof proposed Esperanto; it was intended as a global language to be spoken and understood by everyone. The inventor was hoping that a common language could resolve global problems that lead to conflict. Esperanto as a planned language might have had some success, but today, English is much more universal. 30 countries have it as an official language, and in many other countries it is taught in school and understood fairly well. The internet can be suspected to further increase the adoption of English.

Still, many people can’t speak English. The collected, shared knowledge that makes up the web is therefore only partly accessible to them. The reverse, of course, is true as well. When you surf the web, you will sometimes come across languages and characters you don’t understand – like Chinese, Arabic, Korean, French, German, Italian, Spanish, or Japanese. Would you be able to fluently read these languages, those sites wouldn’t be a dead end for you. You would discover a wealth of knowledge, and more importantly, opinions. If you’re an US citizen, how many Arabic, German or French sources do you read to get a good understanding of how the world sees the US? How many blogs do you read in foreign languages? Probably not many, unless you’re fluent in those languages.

At the recent web cast of the Google Factory Tour, researcher Franz Och presented the current state of the Google Machine Translation Systems. He compared translations of the current Google translator, and the status quo of the Google Research Lab’s activities. The results were highly impressive. A sentence in Arabic which is now being translated to a nonsensical “Alpine white new presence tape registered for coffee confirms Laden” is now in the Research Labs being translated to “The White House Confirmed the Existence of a New Bin Laden Tape.”

Adults often struggle trying to learn a second language, but the process may not be as tedious and slow as commonly believed. University of Washington researchers who followed college students learning first-year French have found that the students' brain activity was clearly discriminating between real and pseudo-French words after only 14 hours of classroom instruction. At the same time, however, the students performed at 50-50 levels when asked to consciously choose whether or not the stimuli were real French words. In addition, the researchers found that as the students had more exposure to French, the difference in brain response to words and pseudo words became larger.

The study, which is one of the first to look at how fast second-language words are learned and how the brain responds to words with increasing experience with the new language, was published June 13 in the on-line edition of the journal Nature Neuroscience. The research team was headed by Judith McLaughlin, a UW research scientist, and Lee Osterhout, an associate professor of psychology. "Age and reduced brain plasticity are the classic reasons usually given for difficulty in learning a second language. But almost all thinking about this concerns syntax and grammar, while word learning has been ignored," Osterhout said.

Real communication with animals could happen sooner than you think.

Human beings have long studied the myriad ways by which animals communicate and interact with one another. Significant research has explored body language and vocalization; the importance of color, scent, and touch; the significance of territorial and mating rituals; and a host of other communications patterns that signify health, environment, and relationship.

In recent decades, researchers all over the world have studied animal communication patterns that appear to approximate human communication. Work on hummingbirds, songbirds, and parrots has shown their ability to learn and continue learning new sounds and to use syntax to arrange them in ever more complex ways. With higher animals, scientists continue to make great strides in understanding the more sophisticated communication patterns of such animals as dolphins, whales, and great apes.

For decades, the human race has invested substantial resources in exploring the depth of the universe while searching for extraterrestrial intelligence but, so far, there has been no contact. What would happen if, instead of focusing on communicating with extraterrestrial intelligence, we used our resources and computer technology to make the fictional achievements of Doctor Dolittle a reality?

This possibility is not science fiction; it is quite likely to become a reality on a significant scale within a decade or two. Many aspects of technology—from the speed of computing to more-intelligent sensors to nanotechnology—are coming together to make a breakthrough increasingly likely. And this breakthrough could happen even sooner than we think if humanity has the will and foresight to make it happen.

Once upon a time, there were very few human languages and perhaps only one, and if so, all of the 6,000 or so languages spoken round the world today must be descended from it.

If that family tree of human language could be reconstructed and its branching points dated, a wonderful new window would be opened onto the human past.

Yet in the view of many historical linguists, the chances of drawing up such a tree are virtually nil and those who suppose otherwise are chasing a tiresome delusion.

Languages change so fast, the linguists point out, that their genealogies can be traced back only a few thousand years at best before the signal dissolves completely into noise: witness how hard Chaucer is to read just 600 years later.

But the linguists' problem has recently attracted a new group of researchers who are more hopeful of success. They are biologists who have developed sophisticated mathematical tools for drawing up family trees of genes and species. Because the same problems crop up in both gene trees and language trees, the biologists are confident that their tools will work with languages, too.

The key cognitive step that allowed humans to become the only animals using language may have been identified, scientists say.

A new study on monkeys found that while they are able to understand basic rules about word patterns, they are not able to follow more complex rules that underpin the crucial next stage of language structure.

We paraphrase all the time, often without thinking about it. Try to give a computer the means to reword a sentence, however, and it becomes apparent that figuring out how to say it differently is complicated.

Researchers at Cornell University have tapped a pair of unlike sources -- on-line journalism and computational biology -- to make it possible to automatically paraphrase whole sentences. The researchers used gene comparison techniques to identify word patterns from different news sources that described the same event.

The method could eventually allow computers to more easily process natural language, produce paraphrases that could be used in machine translation, and help people who have trouble reading certain types of sentences.

Bow (or libbow) is a library of C code useful for writing statistical text analysis, language modeling and information retrieval programs. The current distribution includes the library, as well as front-ends for document classification (rainbow), document retrieval (arrow) and document clustering (crossbow).

Conflicting needs may have driven rapid development of communication.

Language probably leapt, not crept, from squeaks to Shakespeare, two physicists have calculated. Human communication, they propose, underwent a 'phase transition', like solid ice melting to liquid water.

The richness of human languages is a fine-tuned compromise between the needs of speakers and of listeners, explain Ramon Ferrer i Cancho and Ricard Sol� of the Universitat Pompeu Fabra in Barcelona. Just a slight imbalance of these demands prevents the exchange of complex information, they argue.