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"But the speed of the typists' keystrokes revealed something else. After hitting the wrong key, a typist's fingers slowed down for the next keystroke, even if the researchers sneakily fixed the error so that the typist didn't notice it. In these cases, a typist wasn't explicitly aware of the mistake, but the brain's motor signal changed nevertheless."

'By studying language in people with aphasia, we can try to accomplish two goals at once: we can improve our clinical understanding of aphasia and get new insights into how language is organized in the mind and brain,' said Daniel Mirman, Professor of Psychology at Drexel University. Mirman is lead author of a new study which examined data from 99 people who had persistent language impairments after a left-hemisphere stroke. In the first part of the study, the researchers collected 17 measures of cognitive and language performance and used a statistical technique to find the common elements that underlie performance on multiple measures. Researchers found that spoken language impairments vary along four dimensions or factors: 1. Semantic Recognition: difficulty recognizing the meaning or relationship of concepts, such as matching related pictures or matching words to associated pictures. 2. Speech Recognition: difficulty with fine-grained speech perception, such as telling "ba" and "da" apart or determining whether two words rhyme. 3. Speech Production: difficulty planning and executing speech actions, such as repeating real and made-up words or the tendency to make speech errors like saying "girappe" for "giraffe." 4. Semantic Errors: making semantic speech errors, such as saying "zebra" instead of "giraffe," regardless of performance on other tasks that involved processing meaning. In the second part of the study, researchers mapped the areas of the brain associated with each of the four dimensions identified above.

How can mispronunciation of a word today can become tomorrow's strongly defended norm

Journalist David Shariatmadari examines mispronunciations and malapropisms and how they contribute to language change.

This article explains key principles and strategies for how to learn languages. It talks about the important elements: comprehensible input (understanding), comprehensible output (producing), and review/feedback (identifying and correcting errors). It mentions the need for balance and avoiding putting too much effort on one skill. It also talks about the importance of embracing mistakes, being comfortable with not knowing certain things, and creating low-stakes practices to become more comfortable with errors. It talks about motivation in learning and the drive for people's desire to learn the language. It includes a lot of psychology in it too.

National Public Radio interviewed linguist John McWhorter on words and semantic change. The interview provides several contemporary examples showing how words and language are constantly changing. Mc Whorter asserts, "I think that we should learn not to listen to people using natural language as committing errors because there's no such thing as making a mistake in your language if a critical mass of other people speaking your language are doing the same thing."

By Leonardo VintiñiEpoch Times Staff Perhaps the most important job for a copy editor is to ensure that text is free of spelling mistakes. But is error-riddled text any less understandable? On repeated occasions researchers have found that people can still understand the meaning of sentences even if they are completely made up of jumbled words.

Botched autocorrects are a byproduct of a technological convenience that allows typing on the go, even when the message does not always come out as planned. Yet as autocorrect technology has become more advanced, so have its errors. Tech companies like Google, Facebook and Apple employ dozens of linguists - or "natural language programmers," as they are known - to analyze language patterns and to track slang, even pop culture. And they can do amazing things: correct when you hit the wrong keys (the "fat finger" phenomenon) and analyze whom you are texting, how you have spoken with that person in the past, even what you've talked about. Apple's iOS 8 operating system, released in September, even purports to know how your tone changes by medium - that is, "the casual style" you may use in texting versus "the more formal language" you are likely to use in email, as the company put it in a statement. It adjusts for whom you are communicating with, knowing that your choice of words with a buddy is probably more laid-back than it would be with your boss. Your smartphone may now be able to suggest not just words but entire phrases. And the more you use it, the more it remembers, paying attention to repeated words, the structure of your sentences and tone.

People who speak more than one language fluently will process maths (yes, that word is correct: very British!) differently when they switch between languages, a new study has found. The study examined Belgians who are dual-fluent in German and French. While they were able to solve the simple tasks with equal proficiency, they took longer to calculate the complex task in French and made more errors than they did when doing the identical task in German. Different regions of the brain were in use when the participants were solving problems in different languages--no surprise, more cognitive effort was needed when using a second language.

The hallmark of President Trump's Twitter feed is that it sounds like him - grammatical miscues and all. But it's not always Trump tapping out a Tweet, even when it sounds like his voice. West Wing employees who draft proposed tweets intentionally employ suspect grammar and staccato syntax in order to mimic the president's style, according to two people familiar with the process. They overuse the exclamation point! They Capitalize random words for emphasis. Fragments. Loosely connected ideas. Trump's staff has become so adept at replicating the President's tone that people who follow his feed closely say it is getting harder to discern which tweets were actually crafted by Trump sitting in his bathrobe and watching "Fox & Friends" and which were concocted by his communications team. Staff-written tweets do go through a West Wing process of sorts. When a White House employee wants the president to tweet about a topic, the official writes a memo to the president that includes three or four sample tweets, according to those familiar with the process. Those familiar with the process wouldn't fess up to which tweets were staff-written. But an algorithm crafted by a writer at The Atlantic to determine real versus staff-written tweets suggested several were not written by the president, despite the unusual use of the language.

Neuroimaging studies suggest that sign languages are complex linguistic systems processed much like spoken languages, even though they're gestural/visual, not oral. Wernicke's area activates when perceiving sign language; Broca's when producing sign language. In deaf people, lesions in left hemisphere "speech centres" like Broca's and Wernicke's areas produced significantly more sign errors on naming, repetition and sentence-comprehension tasks than signers with damaged right hemispheres.

President Joe Biden and Dr. Anthony Fauci mispronounced the new COVID variant at a recent White House speech, calling the variant "omnicron" instead of the Greek letter "omicron." However, linguists explain that this is an expected error, as it is common for humans to take words from other languages and 'nativize' foreign sounds to make it more natural-sounding in their mother tongue. The abundance of English words with the prefix omni- seems to serve like a magnet, drawing in speakers to the similar set of letters and tempting speakers to mispronounce the omi- prefix as "omnicron."

Emojis are emerging as a new form of communication online, mostly used by younger generations as a way to add emotional depth to online communications. A study conducted suggests that while older generations are less confident about using emojis, they are able to interpret them, and use them with minimal errors.

This article discusses the use of AI in learning languages. It discusses the benefits such as corrective feedback and being able to talk about your topic of choice. However, it also mentions some drawbacks such as potential biases and errors.

This article writes general information about the standard measures taken to ensure clear communication, as it is very important in aviation. These measures include speaking slowly (under 100 wpm), highly coded language, and the difficulties that non-native speakers have with Aviation English. The topic that the article studies is the different errors accented and native speakers commit when communication with air traffic controllers.