Language, Cognition, And Computational Models
How do infants learn a language? Why and how do languages evolve? How do we understand a sentence? This book explores these questions using recent computational models that shed new light on issues related to language and cognition. The chapters in this collection propose original analyses of specific problems and develop computational models that have been tested and evaluated on real data. Featuring contributions from a diverse group of experts, this interdisciplinary book bridges the gap between natural language processing and cognitive sciences. It is divided into three sections, focusing respectively on models of neural and cognitive processing, data driven methods, and social issues in language evolution. This book will be useful to any researcher and advanced student interested in the analysis of the links between the brain and the language faculty.
'The deepest questions about language will be solved through cooperation across disciplinary boundaries. Insights from neuroscience, psychology, linguistics, and social science only offer partial explanations. Computer modeling provides an ideal methodology to integrate these diverse insights and put them to the test on real data. This broad collection of papers from leading research groups, contextualised by Thierry Poibeau and Aline Villavicencio, will inspire everyone interested in the cognitive aspects of language processing.' Walter Daelemans, Universiteit Antwerpen
'Although Natural Language Processing could be considered an area of Cognitive Science, the two fields have tended to go their own way as they matured. Yet the interaction between the two areas can be fruitful. Poibeau and Villavicencio have to be credited for playing an important role in keeping the connection between the two fields alive. The well-chosen and insightful papers in this book provide a great illustration of how the interaction between the two fields can lead to progress in a number of areas from language acquisition to parsing to the diagnosis of cognitive deficits, to the new area of using language models to gain insights about how the brain encodes semantics, and vice versa.' Massimo Poesio, Queen Mary University of London
'This volume brings a uniquely interdisciplinary approach to its subjects … All of the essays present new and emerging research in neuroscience and language. While the materials covered are advanced for most undergraduates, this volume would make a valuable resource for researchers in the field and a helpful guide to graduate students on subjects for further research. An excellent addition to collections where natural language processing and cognitive science are studied. Summing Up: Recommended.' R. Bharath, Choice
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× Product detailsPart I. About This Book:1. Introduction T. Poibeau and A. VillavicencioPart II. Models of Neural and Cognitive Processing:2. Light-and-deep parsing P. Blache3. Decoding language from brain B. Murphy, A. Fyshe and L. Wehbe4. Graph theory applied to speech N. B. Mota, M. Copelli and S. RibeiroPart III. Data-Driven Models:5. Putting linguistics back into computational linguistics M. Kay6. A distributional model of verb-specific semantic roles inferences G. E. Lebani and A. Lenci7. Native language identification on EFCAMDAT X. Jiang, Y. Huang, Y. Guo, J. Geertzen, T. Alexopoulou, L. Sun, A. Korhonen8. Evaluating language acquisition models L. Pearl and L. PhillipsPart IV. Social and Language Evolution:9. Social evolution of public languages A. Reboul10. Genetic biases in language R. Janssen and D. Dediu11. Transparency versus processing efficiency R. Van Trijp.
Thierry Poibeau, Centre National de la Recherche Scientifique (CNRS), ParisThierry Poibeau is Director of Research at Centre National de la Recherche Scientifique (CNRS), Paris and head of the LaTTiCE laboratory in Paris, France. His is also an affiliated lecturer at the Department of Theoretical and Applied Linguistics (DTAL) of the University of Cambridge. He works on natural language processing (NLP), in particular focusing on information extraction, question answering, semantic zoning, knowledge acquisition from text, and named entity tagging.
Aline Villavicencio, Universidade Federal do Rio Grande do Sul, BrazilAline Villavicencio is a Reader at the Institute of Informatics, Universidade Federal do Rio Grande do Sul, Brazil, and is a fellow of CNPq (Brazil). Her research interests in natural language processing are in computational models of acquisition of linguistic information from data, distributional semantic models, multiword expression, and applications like text simplification and question answering.
ContributorsT. Poibeau, A. Villavicencio, P. Blache, B. Murphy, A. Fyshe, L. Wehbe, N. B. Mota, M. Copelli, S. Ribeiro, M. Kay, G. E. Lebani, A. Lenci, X. Jiang, Y. Huang, Y. Guo, J. Geertzen, T. Alexopoulou, L. Sun, A. Korhonen, L. Pearl, L. Phillips, A. Reboul, R. Janssen, D. Dediu, R. Van Trijp
What Is Natural Language Processing (NLP)?
Are you intrigued by the fascinating realm of human-computer interaction? Perhaps, you've found yourself wondering how technologies like Siri or Alexa understand your speech and respond almost like a fellow human. This quick guide will will provide an introduction to the technology behind this phenomenon: Natural Language Processing (NLP). If you have been using ChatGPT or similar AI models the answers you have been receiving have been created using NLP.
Natural Language Processing is an invaluable asset in our technologically advancing world. It serves as the bridge for meaningful interaction between humans and computers. Understanding its principles and its application in today's world can provide valuable insights for both enthusiasts and experts alike.
What is Natural Language Processing?Simply put, NLP is making our interactions with machines smoother and more natural. So, the next time you ask Siri for the weather forecast or Google for a quick translation, remember the remarkable technology at work.
Natural Language Processing, or NLP, is a field in artificial intelligence that aims to create meaningful communication between humans and computers using natural language. Natural language, in contrast to the formal languages that computers inherently understand, refers to the languages that humans use daily.
Remember, NLP is an evolving field. Always keep an eye out for the latest trends and advancements. Because with NLP, it's not just about understanding computers—it's about making them understand us.
Breaking down NLPNLP involves several aspects, each contributing to the bigger picture of effective human-computer communication.
You will be pleased to know that NLP is the driving force behind several applications and tools we use daily. These include:
If you are wondering how to implement NLP in your applications, there are numerous libraries and tools available to help. Python, for example, has libraries such as NLTK (Natural Language Toolkit) and SpaCy. These libraries provide functionalities for tokenizing, parsing, and semantic reasoning, among other tasks.
Challenges in NLPLike any technology, NLP comes with its challenges. Here are a few:
If you would like to improve your NLP outcomes, a good place to start is with your data. Ensure you have a large and diverse dataset. Regularly testing and refining your algorithms can also help improve accuracy.
How does ChatGPT use NLP?ChatGPT, utilizes NLP at its core. It's a sophisticated application of Transformer-based models, which is a class of NLP models known for their capacity to understand context within the text. Here's a brief rundown of how it uses NLP:
Text ProcessingThe first step in the process involves breaking down the input text into smaller units, often words or even smaller elements like subwords, a process known as tokenization. This allows the model to work with text in a manageable, structured format.
Understanding ContextChatGPT then uses the Transformer model architecture to understand the context of the input. The Transformer model looks at all tokens in the text at once, which allows it to understand the relationships and dependencies between different words in a sentence.
Generating a ResponseOnce it understands the text, the model uses the probabilities it has learned during training to generate a response. This involves predicting what word (or token) comes next in a sequence. It does this repeatedly, generating words one after the other until it reaches a set endpoint.
Fine-TuningChatGPT has been fine-tuned on a dataset containing a diverse range of internet text. However, it does not know specifics about which documents were in its training set or have access to any personal data unless explicitly provided in the conversation.
It's important to note that while ChatGPT can generate responses that seem knowledgeable and understanding, it doesn't have beliefs or desires. It generates responses based on patterns it learned during training.
Through this application of NLP, ChatGPT can participate in a conversation, understand the context, and provide relevant responses. It's a perfect example of how NLP is helping to bridge the gap between humans and machines.
Development of Natural Language ProcessingWith constant advancements, NLP is fast becoming integral to numerous technologies. We can expect to see improvements in voice recognition, context understanding, and even in generating human-like text. This exciting field is set to revolutionize how we interact with machines in the future.
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Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.AR Pioneer Gravity Jack Unveils Plan To Reach People Of Every Language Through War Tribe Of Binyamin Game
Gravity Jack will use its soon-to-be-released game, War Tribe of Binyamin, to create natural language processing models that enable translation of knowledge into more than 7,100 less-used languages.
Spokane, Washington --News Direct-- Prodigy Press Wire
Augmented reality (AR) gaming company Gravity Jack has announced its plan to create natural language processing (NLP) models that can translate to every single language in the world,
According to Gravity Jack founder and chief visionary officer Luke Richey, there are more than 7,200 languages in the world, and half of the global population speaks the top 100 most widespread languages. This means that 50% of the world has the remaining 7,100 languages as their first language. While many speak at least one of the top 100 languages, this is not their "heart language". Research shows that 72.4% of consumers are more likely to buy a product if it were presented in their heart language, which shows the huge untapped potential in communicating to people using the language that most naturally comes to them. However, it is not economically viable to create NLP models for these languages, so tech giants concentrate only on the top 100 most-spoken languages.
Richey says that Gravity Jack is looking to solve this problem through its upcoming augmented reality game, War Tribe of Binyamin, which is slated to enter its beta testing phase in Spring 2024. The game, which is playable on mobile devices and AR glasses, combines a number of gaming techniques and genres to provide a fun experience for all age groups, while simultaneously economically uplifting people in poverty and tapping a new market.
The lore of the game involves a millennia-spanning war between two opposing artificial intelligences – the malevolent Aizazel and the benevolent Yamin. Players are part of a faction called Binyamin (Sons of Yamin) who fight against Aizazel to save humanity from being taken over by the machines.
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War Tribe of Binyamin uses Gravity Jack's patented technology for high-resolution location determination without the use of GPS, which will allow the game to dynamically overlay player avatars and information over their own bodies or bodies of other players – a capability that sets Gravity Jack apart from competitors.
Gravity Jack created what it calls the Yamin Uplift Engine solution, which is a plan to reach every global language in a five-year span. Yamin Uplift Engine will harness the revenue from gamers in strong economies, with an estimated average monthly spend of $76 per player (in the US). It will then distribute a large portion of in-game revenue from in-app purchases, into a treasury that automatically pays 10% into a dividend to shareholders, while 55% goes to fund translation of important textual works, such as classic novels, religious texts, and scientific information, into less-used languages. The remaining 35% will be for the game's development and upkeep costs.
The translation works through a system of geo-targeted in-game translation quests. For example, a player in Ethiopia would receive a quest requiring Oromo language translation. By performing these quests, players can receive in-game currency, which can be exchanged into real-world currency through a controlled exchange system. According to Gravity Jack, all translation work will be performed by natives of the language using the game, and it includes a five-fold verification process to ensure valid translation. The information gathered through the quests will be used to create an NLP engine to accurately translate into that language.
Over time, Gravity Jack aims to build up adequate datasets for machine learning natural language processing engines for the 7,100 other languages, a feat that's otherwise would not be economically viable.
"We've been in the AR space since the technology's infancy, and we're bringing our extensive expertise to create a game that will demonstrate the full capabilities of augmented reality through an immersive gaming environment. Through our Yamin Uplift Engine, we are creating a way to translate knowledge into languages that the tech giants ignore, as well as providing economic incentives for people in low-income economies," Richey says.
Media contact:
Name: Luke Richey
Email: [email protected]
Release ID: 666738
View source version on newsdirect.Com: https://newsdirect.Com/news/ar-pioneer-gravity-jack-unveils-plan-to-reach-people-of-every-language-through-war-tribe-of-binyamin-game-660287990
