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Voice-based interactions require sophisticated programming and AI to enable a machine to understand and talk to you. In other words, it's a really big deal to program a computer to have a conversation. Walter says the challenge now is to process massive amounts of dialogue-related data to facilitate human-like intellectual and speech functionality in machines. "We are developing the technology that will give machines the cognitive ability to understand the semantics and context of a conversation, respond to topic changes and, in essence, carry on everything from a complex conversation to small talk."

Choosing a voice has implications for design, branding or interacting with machines. A voice can change or harden how we see each other. Research suggests that users prefer a younger, female voice for their digital personal assistant. We don't just need that computerized voice to meet our expectations, said Justine Cassell, a professor at Carnegie Mellon's Human-Computer Interaction Institute. We need computers to relate to us and put us at ease when performing a task. "We have to know that the other is enough like us that it will run our program correctly," she said. That need seems to start young. Ms. Cassell has designed an avatar of indeterminate race and gender for 5-year-olds. "The girls think it's a girl, and the boys think it's a boy," she said. "Children of color think it's of color, Caucasians think it's Caucasian." Another system Cassell built spoke in what she termed "vernacular" to African-American children, achieving better results in teaching scientific concepts than when the computer spoke in standard English. When tutoring the children in a class presentation, however, "we wanted it to practice with them in 'proper English.' Standard American English is still the code of power, so we needed to develop an agent that would train them in code switching," she said. And, of course, there are regional issues to consider when creating a robotic voice. Many companies, such as Apple, have tweaked robotic voices for localized accents and jokes.

Why do Jane Austen's literary works endure some 200 years after her death? The Stanford Literary Lab ran computational analysis on the words contained in Austen's work. Eschewing the fantastical and dramatic elements typical of novels both in Austen's lifetime and ours, Austen is more concerned with social realities and human nature. Her works display emotional intelligence; she employs more words about emotions and time, as well as abstract words connected to states of mind and social relationships.

"Koko, arguably the world's most famous gorilla, has died at the age of 46. Known for her ability to communicate through sign language, Koko forever changed our conceptions of primate intelligence and emotional capacities."

Metaphors are extremely useful things. They provide a common language-an agreed-upon shorthand-for truths that can be difficult to discuss in terms that are simultaneously broad and precise. It doesn't take a Lakoff or a Luntz to appreciate the power of shared metonyms, particularly as the country grapples with the results of an election that was a political embodiment of that well-worn Fitzgerald line: "The test of a first-rate intelligence is the ability to hold two opposed ideas in the mind at the same time, and still retain the ability to function." This election, in particular, featured many more than two oppositional ideas. The 2018 midterms were about voter suppression, which is also to say about robbing swaths of Americans of their constitutional rights, which is also to say about structuralized inequality. They were about enfranchisement and its opposite. They were about progress. They were about backlash. They were about women winning. They were about women losing. They were about compassion empowered, and racism rewarded, and hard work realized, and cruelty weaponized, and corruption unpunished. They were about hatred. They were about love. They were about history made. They were about history ignored. They were about American exceptionalism in the best sense and-at the same time-in the worst. How do you sum that up in a headline or a news article? How do you talk about it in neatly cable-newsed sound bites? The true answer is that you can't, and the even truer answer is that this is why it is necessary to have a flourishing and extremely diverse media ecosystem, so that a broadly coherent picture might emerge from the individual efforts-but the more practical and immediate answer is that you can try to use metaphors to summarize the situation. You can talk about waves, with their familiarity and their liquidity and their visual power, and you can talk about the color of your notional water, and the size and shape of the swell, and you

Recent History of Our Struggle to Make Foreign Languages Core Foreign language study is in the national education Goals 2000, which states: "By the year 2000 all American students will leave grades 4, 8, and 12 having demonstrated competency in challenging subject matter including English, mathematics, science, foreign language, civics and government, arts, history, and geography..."

This article explains the new system created for air traffic controllers and pilots. AcListant is a system that will listen to air controllers' radio conversations to help make suggestions for commands that fit the situation. The system can filter through basic greetings like "Hello" and "Good Morning" and focus on commands instead. AcListant can help with better communication especially with pilots who speak very fast or with an accent.

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."

This article explains how close we are getting to understanding Dolphin's language. They language consists of sentences, similar to ours, where the order of the words determine the meaning of the sentence. They also apparently take turn talking, as we do. So all scientists need to do now is figure out what meaning matchings each sound. This is where AI (aka. Artificial intelligence) comes in. Scientists will be using one to help figure out meanings to sounds. This will be taking place in a wildlife park south of Stockholm to Bottlenose dolphins.

Google assistant (an intelligent personal assistant app developed by Google) will, starting this summer, be able to detect and respond in French, German, Brazilian-Portuguese and Japanese. And by the end of the year, the Assistant will also be able to speak Italian, Spanish and Korean. Opening the product to people who don't speak English

A team of researchers from Rice University and University of Maryland, College Park argue that it is more productive from a developmental perspective to describe spoken language as a special type of music. A review of existing studies presents a compelling case that musical hearing and ability is essential to language acquisition. In addition, we challenge the prevailing view that music cognition matures more slowly than language and is more difficult; instead, the researchers argue that music learning matches the speed and effort of language acquisition, and indeed, that "it is our innate musical intelligence that makes us capable of mastering speech." They conclude that music merits a central place in our understanding of human development.

The researchers of this study advance the idea that spoken language is introduced to the child as a vocal performance, and children attend to its musical features first. Without the ability to hear musically, it would be impossible to learn to speak. In addition, they question the view that music is acquired more slowly than language (Wilson, 2012) and demonstrate that language and music are deeply entangled in early life and develop along parallel tracks. Rather than describing music as a "universal language," they find it more productive from a developmental perspective to describe language as a special type of music in which referential discourse is bootstrapped onto a musical framework. Newborn infants' extensive abilities in different aspects of speech perception have often been cited as evidence that language is innate (e.g., Vouloumanos and Werker, 2007). However, these abilities are dependent on their discrimination of the sounds of language, the most musical aspects of speech. Music has a privileged status that enables us to acquire not only the musical conventions of our native culture, but also enables us to learn our native language. Without the ability to hear musically, we would be unable to learn language.

This article provides an insight into an interview with Christopher Manning, a Stanford professor of computer science and linguistics. He is focused on computational linguistics, also known as natural language processing. Natural language processing involves creating algorithms that can allow computers to understand written and spoken language and then intelligently respond. This involves systems such as Siri, Alexa, and Google Voice. These systems are pretty advanced technology, however, they are still far from perfect. Manning notes that people will probably still be working on natural learning processing in twenty years.

Interesting article re: designing an efficient and responsive bot: leveraging key human linguistic features in order to have the machine "converse" with humans, comprehend their needs, and respond appropriately. Programming a machine to exhibit the conversational nuances and sophisticated comprehension of a normal human=hard.

A connection has been found between students who study foreign language and higher SAT scores. For each additional year that students study a foreign language, they are expected to perform better on both the math and language portions of the SAT. Although the SAT is not a direct measure of intelligence by any means, this gives evidence to support that studying a foreign language helps develop both math and English language skills. I would be interested in seeing how foreign language study affects IQ Test scores.

This article shows the potential influence that AI has on the economy. AI uses coding and programming through communication between computers in order to function

This article combines data from two lists. This first one was compiled by National Language Resources Monitoring and Research Center at Beijing Language and Culture University: "Big data analysis" of over a billion online posts and forum discussions from the Chinese internet in 2021 was reportedly used to decide on the final list, but it's clear from the selection that the artificial intelligence tool used has a good understanding of socialism with Chinese characteristics. The second list comes from Yaowen Jiaozi, a magazine founded in 1995 that publishes stories about the the misuse and abuse of language in Chinese society. This combined list has items that made BOTH lists. Separately, the magazine Yǎowén Jiáozì (咬文嚼字) published its year-end list of "popular buzzwords" (2021年十大流行语). Yaowen Jiaozi is a magazine founded in 1995 that publishes stories about the the misuse and abuse of language in Chinese society. Its name is variously translated as "Correct Wording," "Verbalism," and "Chewing Words." The Yaowen Jiaozi list does not claim to be created by big data, but rather from reader suggestions, online polling, and selection by specialists.

This article, published by BYU, talks about the effects that certain accents have on people's perceptions. Because everyone talks in a different way, some cultures may associate people with certain labels. Many studies are conducted within this article that displays statistical data on the perception of certain accents. Some people perceive certain accents positively while others see them negatively. This article reflects how different cultures act while being combined and the outcomes that come out of that action.

This article published from Yale briefly informs the reader about what dyslexia is, and how it can impact a person's everyday life. Something that is very interesting is even though dyslexia can create a setback when interpreting literature, many people who have dyslexia are some of the most creative thinkers. This just proves that the condition cannot define the intelligence of an individual. Even though it cannot be cured, it is very possible to have success and "overcome" this obstacle.