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SwiftKey, a keyboard app, did an analysis of one billion emoji from aggregate SwiftKey Cloud data. The interactive map shows which emoji are most frequently used by which state. The full report can be loaded from https://blog.swiftkey.com/the-united-states-of-emoji-which-state-does-your-emoji-use-most-resemble/.

Article discusses the findings of researchers who've documented and categorized the utterances of the dying (morbid, but true!) Author Michael Erard notes that more research should be done in this area, because "Even basic descriptions of language at the end of life would not only advance linguistic understanding but also provide a host of benefits to those who work with the dying, and to the dying themselves. Experts told me that a more detailed road map of changes could help counter people's fear of death and provide them with some sense of control. It could also offer insight into how to communicate better with the dying. Differences in cultural metaphors could be included in training for hospice nurses who may not share the same cultural frame as their patients."

Of the 7,105 languages spoken today, over half are considered in danger of extinction in this century. As languages vanish, communities lose a wealth of knowledge about history, culture, the natural environment and the human mind. This will be a catastrophic erosion of the human knowledge base, affecting all fields of science, art, and human endeavor. It will also be an incalculable loss to indigenous peoples' sense of history, identity, belonging, and self. The story map embedded in this website will take you on a virtual tour of some endangered language communities around the world, to see and hear some of the last speakers, and understand their struggle to save their languages.

This speech accent archive, headed by Steven Weinberger, a linguistics professor at George Mason University, is a project of the linguistics program in the Department of English, the College of Arts and Science's Technology Across the Curriculum program, and the Center for History and New Media at George Mason University. The archive uniformly presents a large set of speech samples from a variety of language backgrounds. Native and non-native speakers of English read the same paragraph and are carefully transcribed. The archive is used by people who wish to compare and analyze the accents of different English speakers. This website allows users to compare the demographic and linguistic backgrounds of the speakers in order to determine which variables are key predictors of each accent. The speech accent archive demonstrates that accents are systematic rather than merely mistaken speech. Each individual sample page contains a sound control bar, a set of the answers to 7 demographic questions, a phonetic transcription of the sample,1 a set of the speaker's phonological generalizations, a link to a map showing the speaker's place of birth, and a link to the Ethnologue language database. The archive also contains a set of native language phonetic inventories so that you can perform some contrastive analyses.

Researchers from King's College London Institute of Psychiatry, in collaboration with Bellvitge Biomedical Research Institute (IDIBELL) and the University of Barcelona, mapped the neural pathways involved in word learning among humans. They found that the arcuate fasciculus, a collection of nerve fibres connecting auditory regions at the temporal lobe with the motor area located at the frontal lobe in the left hemisphere of the brain, allows the 'sound' of a word to be connected to the regions responsible for its articulation. Differences in the development of these auditory-motor connections may explain differences in people's ability to learn words. Researchers used diffusion tensor imaging to image the structure of the brain before a word learning task and functional MRI, to detect the regions in the brain that were most active during the task. They found a strong relationship between the ability to remember words and the structure of arcuate fasciculus, which connects two brain areas: the territory of Wernicke, related to auditory language decoding, and Broca's area, which coordinates the movements associated with speech and the language processing. In participants able to learn words more successfully their arcuate fasciculus was more myelinated i.e. the nervous tissue facilitated faster conduction of the electrical signal. In addition the activity between the two regions was more co-ordinated in these participants. Dr Catani concludes, "Now we understand that this is how we learn new words, our concern is that children will have less vocabulary as much of their interaction is via screen, text and email rather than using their external prosthetic memory. This research reinforces the need for us to maintain the oral tradition of talking to our children."

A traveling journalist in Beijing utilizes both Baidu (China's version of Google) and Google voice-translation apps with mixed results. You speak into the apps, they listen and then translate into the language you choose. They do it in writing, by displaying text on the screen as you talk; and out loud, by using your phone's speaker to narrate what you've said once you're done talking. Typically exchanges are brief: 3-4 turns on average for Google, 7-8 for Baidu's translate app. Both Google and Baidu use machine learning to power their translation technology. While a human linguist could dictate all the rules for going from one language to another, that would be tedious, and yield poor results because a lot of languages aren't structured in parallel form. So instead, both companies have moved to pattern recognition through "neural machine translation." They take a mountain of data - really good translations - and load it into their computers. Algorithms then mine through the data to look for patterns. The end product is translation that's not just phrase-by-phrase, but entire thoughts and sentences at a time. Not surprisingly, sometimes translations are successes, and other times, epic fails. Why? As Macduff Hughes, a Google executive, notes, "there's a lot more to translation than mapping one word to another. The cultural understanding is something that's hard to fully capture just in translation."

A linguist who began to train her border collie for sheepdog competitions using a dog whistle realized that the commands reminded her of language. The article goes on to detail communication between dogs and people, and how dog's cognition and understanding goes past following basic commands. For example, Chaser, the border collie, was able to fast map and learn things through reference cues - which goes much farther past simply understanding commands. It turns out, shepherds use only a few whistle commands with their sheepdogs, but the whistles change meaning based on situation, pitch, speed, etc, and provide information to the dog, similar to prosody, a key part of human language.

While this article is directed towards teachers, students can leverage this information to their advantage. Employ the following five strategies to aid retention: 1. Teach a friend. When students explain what they've learned to peers, fading memories are reactivated, strengthened, and consolidated. This strategy not only increases retention but also encourages active learning (Sekeres et al., 2016). 2. The spacing effect: Instead of covering a topic and then moving on, revisit key ideas throughout the school year. Research shows that students perform better academically when given multiple opportunities to review learned material. For example, teachers can quickly incorporate a brief review of what was covered several weeks earlier into ongoing lessons, or use homework to re-expose students to previous concepts (Carpenter et al., 2012; Kang, 2016). 3. Frequent practice tests: Akin to regularly reviewing material, giving frequent practice tests can boost long-term retention and, as a bonus, help protect against stress, which often impairs memory performance. Breaking down one large high-stakes test into smaller tests over several months is an effective approach (Adesope, Trevisan, & Sundararajan, 2017; Butler, 2010; Karpicke, 2016). 4. Interleave concepts: Instead of grouping similar problems together, mix them up. Solving problems involves identifying the correct strategy to use and then executing the strategy. When similar problems are grouped together, students don't have to think about what strategies to use-they automatically apply the same solution over and over. Interleaving forces students to think on their feet, and encodes learning more deeply (Rohrer, 2012; Rohrer, Dedrick, & Stershic, 2015). 5. Combine text with images: It's often easier to remember information that's been presented in different ways, especially if visual aids can help organize information. For example, pairing a list of countries occupied by German forces during World War II wi

Sound symbolism is a non-arbitrary relationship between speech sounds and meaning. We review evidence that, contrary to the traditional view in linguistics, sound symbolism is an important design feature of language, which affects online processing of language, and most importantly, language acquisition. We propose the sound symbolism bootstrapping hypothesis, claiming that (i) pre-verbal infants are sensitive to sound symbolism, due to a biologically endowed ability to map and integrate multi-modal input, (ii) sound symbolism helps infants gain referential insight for speech sounds, (iii) sound symbolism helps infants and toddlers associate speech sounds with their referents to establish a lexical representation and (iv) sound symbolism helps toddlers learn words by allowing them to focus on referents embedded in a complex scene, alleviating Quine's problem. We further explore the possibility that sound symbolism is deeply related to language evolution, drawing the parallel between historical development of language across generations and ontogenetic development within individuals. Finally, we suggest that sound symbolism bootstrapping is a part of a more general phenomenon of bootstrapping by means of iconic representations, drawing on similarities and close behavioural links between sound symbolism and speech-accompanying iconic gesture.

Keeping in touch is no longer about face to face, but instead screen to screen, highlighted by the fact that more than 1 billion people are using Facebook every day. Social media has become second nature -- but what impact is this having on our brain? "In a recent study, researchers at the UCLA brain mapping center used an fMRI scanner to image the brains of 32 teenagers as they used a bespoke social media app resembling Instagram. By watching the activity inside different regions of the brain as the teens used the app, the team found certain regions became activated by "likes", with the brain's reward center becoming especially active." This article goes into depth on how social media like instagram is changing our brain. It shows us what parts of our brain are getting stimulated when we use social media! It also talks about peer influence, social learning, and reward circuitry.

This article talks about the ASL-LEX database that four scientists created. The map of signs is meant to represent a mental lexicon and is allowing them to examine how signs are organized in the human mind. The article explains that signs may rhyme in a visual way even though the words do not, which causes the brain to relate groups of signs together. One pattern that was noticed is that the more commonly used signs tend to be simpler and shorter than the rare ones, which is comparable to spoken language. They also found that common signs are more likely to be in clusters of visually similar words, while rare signs are more isolated.

New research on language acquisition in babies leads scientists to believe that babies map sounds and critical aspects of their language before they begin speaking.