Articles tagged with Semantics
A University of Houston researcher disputes a study claiming multilingualism promotes healthy brain aging, finding that wealth and healthcare systems may drive longevity instead. Hernandez argues that individual behavioral solutions, such as learning a language, are oversold and distract from structural factors that support healthy aging.
Researchers have found that babies can detect verb inconsistencies as early as 10 months old, using brain imaging technology. This finding suggests that infants begin to develop an understanding of verbs before they even say their first words.
A large-scale study reveals that generative AI models have reached the threshold of average human creativity, but the most creative individuals still outperform even the best AI systems. The study also highlights the importance of human guidance and parameterization in modulating AI creativity.
New study finds psychosis delusions emerge from emotional experiences, bodily reactions, and linguistic fabric. Participants described intense emotional embodiment and disembodiment, with some experiencing positive feelings of awe and love.
The verb kikoyu, originally meaning 'to hear', came to represent approximate understanding, then general understanding, and finally conviction. This process reflects cognitive simulation and mental representation transformation.
Street art in Kaunas, Lithuania acts as a form of cultural activism and collective memory, blending languages, images, and historical narratives. Murals have become powerful tools for community reflection and dialogue, turning public space into a living archive of cultural identity.
A new study published in JNeurosci used fMRI to investigate how the brain acquires semantic information. The results suggest that the quality of activity in distinct brain regions can predict whether people successfully acquire knowledge about places and characters in fictional civilizations.
Researchers Marie Teich and Wilmer Leal develop a formal framework to analyze metaphors, confirming they are enduring linguistic and cognitive structures. The study reveals two significant metaphorical processes: mappings from concrete to abstract topics and the emergence of new mappings between domains.
Researchers found that humans across cultures and languages break their speech into Intonation Units, which follow a low-frequency rhythm of 1.6 seconds. This universal structure plays a critical role in helping listeners follow conversations and absorb information.
A team of researchers combined artificial intelligence and statistical modeling to analyze language patterns in three major sections of the Bible. They distinguished between three distinct scribal traditions spanning the first nine books of the Hebrew Bible, known as the Enneateuch. The model also determined the most likely authorship ...
A novel optical semantic communication system using multimode fiber was developed to enhance data transmission capacity and robustness. The system demonstrated a seven-fold increase in transmission capacity compared to conventional methods, and improved noise tolerance for sentiment analysis applications.
A new study found that speech sounds have texture and shape to them, with R sounds associated with roughness and L sounds with smoothness. The research showed strong tendencies for matching trilled R sounds with jagged lines and L sounds with straight lines across cultures.
A study found that large language models (LLMs) like ChatGPT underperform state-of-the-art detectors but can explain their analysis in plain language. LLMs' semantic knowledge makes them well-suited for detecting deepfakes, providing a common sense understanding of reality.
Research by Lancaster University found that people in higher social grades, including corporate world and education sectors, are adopting each other's speech patterns to be more inclusive. This 'resonance' has increased over the past 20 years, particularly among those with high social status.
Researchers create special language Phenoscript to describe traits in a way that both humans and computers can understand. This allows for large-scale studies of organismal traits, boosting the emerging field of phenomics. The new language is being tested and aims to integrate semantic species descriptions with nanopublications.
According to MSU research, linguistically simple headlines engage readers more than complex ones. The study found that simplicity impacts how often people click on stories, leading to increased demand for good journalism. By writing simply, news organizations can make their content more approachable and accessible to a wider audience.
Identical odors are processed differently in the brain based on their assigned labels, according to new research. The study found that participants rated odors with different names as more dissimilar than those labeled with the same name.
The study reveals that experienced programmers exhibit brain responses similar to those of fluent readers processing sentences, indicating a strong resemblance between learning computer and natural languages. The research suggests that understanding how people learn to code can be informed by expertise in second-language learning.
A recent study by Tokyo University of Science has identified central emotions across languages through word association-based colexification networks. The researchers found that concepts like GOOD, WANT, BAD, and LOVE are associated with many other words representing emotions.
Researchers at Lancaster University find that the 'r' sound is becoming weaker in England, with most young speakers softening it to an elongation of the vowel. This decline is predicted to continue, potentially erasing traditional dialects and linguistic homogenization.
Researchers created a large-scale remote sensing annotation dataset to support Earth observation research and monitor global land cover changes. The Globe230k dataset provides new insights into the dynamic monitoring of global land cover, enabling high-level semantic understanding of land use.
Researchers compiled personal reports and associations from 132 participants to categorize 1,001 self-portraits into 26 categories. Five clusters emerged, including 'aesthetics', 'imagination', and 'trait', which showed a close association with visual language used to communicate different aspects of oneself.
A new study from UTHealth Houston has found that the posterior temporal cortex and inferior frontal cortex are crucial for semantic integration during reading. This discovery may help illuminate the inner dynamics of aphasia, a disorder affecting language expression and comprehension.
A linguistic phenomenon reveals specific rules governing sentence construction, shedding light on universal features of human language. The researchers found that 'whom of which' obeys strict rules, contributing to a larger discussion about syntax and the existence of pied piping.
Biodiversity researchers can now incorporate nanopublications into their manuscripts to future-proof their assertions on biological taxa and organisms. The newly released nanopublication workflow enables authors to create machine-actionable, FAIR data that can be easily traced back to its origin.
A new dictionary provides a comprehensive overview of Shakespeare's language, revealing words with reduced mental ability and plant hybrids. The Arden Encyclopedia of Shakespeare's Language offers insights into the linguistic thumbprints of plays and characters, as well as the networks of character interaction.
A study by University of Toronto researchers found that child language development and language evolution share a common cognitive foundation, based on a core knowledge base. The team built a computational model that predicts word meaning extension patterns across languages and time scales, highlighting the role of visual, associative,...
Researchers argue that emoji-based language systems can improve communication between patients and physicians, particularly for vulnerable populations such as those with stroke or vocal impairments. The use of emoji can condense surveys and questionnaires, increasing response rates and appealing to patients.
Researchers at the University of Texas at Austin developed a semantic decoder that translates brain activity into text, allowing individuals with speech disabilities to communicate. The system has been trained on extensive hours of podcasts and can decode continuous language, capturing the gist of what is being said or thought.
A new study reveals that online hate speech is frequently conveyed through subtle and modified wording, allowing it to evade detection. Covert methods of expression are being used by haters to avoid detection, highlighting the need for increased attention to implied ways of expressing hate.
Researchers have found that Khanty dialects consist of three distinct languages, rather than two, with basic vocabulary coincidences lower than those between certain Slavic languages. Idalia Fedotova's study using 110 basic concepts and 14 sources found dialectal groups to be separate languages due to low coincidence rates.
A novel multi-modal image retrieval system, DenseBert4Ret, has been developed by researchers from Gwangju Institute of Science and Technology (GIST) using deep learning algorithms. The system outperforms state-of-the-art models in retrieving images based on both image and text features.
Researchers at Stockholm University developed a fully automatic method to categorize English smell words into offensive, malodorous, fragrant, and edible smells. The study's findings have great potential for standardizing vocabularies in the food and perfume industries.
Researchers discovered that humans automatically integrate extralinguistic information into grammatical processing, improving communication. The study used EEG data from 37 native Russian speakers, finding both linguistic and extralinguistic features processed simultaneously.
Researchers at the University of Basel developed a method to determine how risk is perceived within a society. The study found that threat and fortune are the most prominent components of risk, with threat being more closely associated with older people and women. The results also indicate that there are universal correlations in risk ...
Researchers found that bilinguals process linguistic information in their second language automatically and simultaneously, using left temporo-parietal neural regions. The study uses EEG data to show that Russian primes increase reaction times for English targets, indicating cross-language activation.
Research by University of Cambridge academics found that children as old as five or six struggle to reconcile inference and perspective, leading to difficulties in conversations. Combining these skills is crucial for understanding 'implicatures' - inferences made in conversation when people mean more than they say.
An interdisciplinary team has created a large public database of standardized wordlists for over 2000 language varieties, providing insights into the structure of human languages. The data reveals patterns of independent parallel evolution in linguistic diversity, with many languages using similar words for related concepts.
A study by Tokyo University of Science researchers used WCNs with increasing n values to find features of language that cannot be analyzed using existing WCNs. They found important features in networks with more than three co-occurrences, independent of text data.
Researchers observed that English accounted for 61% of time, while Spanish had 39%, indicating a greater proportion of corrections were made when speaking in English. This study highlights the need for balanced tasks that consider these differences to benefit both students learning English and Spanish.
Researchers from HSE School of Linguistics and Centre for Language and Brain conducted an experiment to understand how language speakers perceive polysemous words. The proximity of figurative senses to the literal sense affects perception as semantically different.
The Swiss team proposes a three-pillar strategy for semantic framework development, compositional language creation, and adaptation to specific data models. This approach aims to unify vocabularies and facilitate cross-referencing of mutually intelligible data from different sources.
A recent study found that artificial neural networks develop spontaneous systems to name colours, adopting similar behaviours to humans. The researchers identified a universal property of optimizing complexity/accuracy trade-offs in discrete communication systems.
Osaka University researchers use deep learning to improve mobile mixed reality generation, enabling the automatic removal of obstructions and addition of greenery. This technology may revolutionize green architecture and city revitalization by providing real-time visualizations.
The study found that cathodal tDCS enhances the acquisition of abstract semantics, while anodal tDCS shows more success in learning concrete concepts. The results suggest that different neural mechanisms are involved in processing abstract and concrete word meanings.
Researchers have created an algorithm that significantly reduces the time taken to analyze HeLa cancer cells using Electron Microscopy. The new approach uses deep learning architectures and achieves results in minutes, compared to a week for human experts.
A machine learning study conducted at Princeton University found that the meaning of words is shaped by culture, history, and geography. The researchers analyzed over 1,000 words in 41 languages and discovered that many everyday words have varying meanings across cultures.
A Carnegie Mellon-developed navigation system, SemExp, uses machine learning to train robots to recognize objects and understand their locations in a home. This enables the system to think strategically about how to search for something, making it more efficient than classical robotic navigation systems.
Researchers create 3D Dynamic Scene Graphs, enabling robots to quickly generate maps of their surroundings and extract relevant information. The new model is modeled after human perception and allows robots to navigate and make decisions like humans.
A study by University of Colorado Denver found that affirmative action's legal semantics have redefined diversity priorities to benefit white students. This shift is reflected in initiatives like 'Inclusive Excellence,' which treats students of color as responsible for diversity, rather than promoting true inclusivity.
Distributional semantics provides radically empirical representations of words' meanings by processing thousands of texts. Research by Gemma Boleda highlights its potential to advance knowledge on how language works, including detecting changes in meaning over time.
Researchers used a database of 2474 languages to study emotion concepts, revealing wide variation in emotional states but also universal structure constraining these concepts. This study provides evidence for the role of both cultural and biological evolution in shaping human emotions.
Researchers mapped emotion words across 2,474 languages to find significant variation in emotional expression across cultures. The human experience of emotions is shaped by both biological evolution and the words used to describe those feelings.
Researchers create method that enables robots to use environmental clues to plan routes, reducing time spent exploring properties and eliminating the need for maps of specific residences. The approach leverages pre-existing algorithms to generate a new map of the environment as the robot moves around, represented as semantic clues.
Research using functional MRI found that brain activity for spoken and written words is nearly identical, adding to understanding of language processing. The study's results support the idea that the same areas of the brain process semantic information regardless of sense modality.
A study with 24 participants aged 18-30 used fMRI scans to map brain areas involved in reading written words in two artificial alphabets. The results showed a hierarchy of brain regions, with posterior regions encoding letter position within words and left mid-to-anterior regions processing phonological and semantic information.
Researchers developed a machine-learning method to quantify semantic richness of conversational language, predicting psychosis with high accuracy. They analyzed sound-related words and low semantic density, detecting hidden patterns in people's language predictive of psychosis.
MORPHEUS, a new processor architecture, blocks potential attacks by encrypting and randomizing key bits 20 times per second. This makes vulnerabilities virtually impossible to exploit, providing a future-proof secure system.
Researchers at Aalto University studied how listeners immerse themselves in audiobooks using fMRI and word lists. The study found that similar words in a list predicted similarities in brain activity, particularly in language processing and visual cortex areas.
Research reveals distinct brain regions process concrete and abstract word meanings separately, with a network of areas working together in different languages. The findings provide new insights into how our brains represent word-meaning structure.