Computational linguistics is an interdisciplinary field between linguistics and computer science that deals with computational modeling of human language. It has both theoretical and applied components. Theoretical CL develops formal models of linguistic knowledge and implements them as computer programs to better understand language faculties. Applied CL focuses on practical applications like natural language interfaces and machine translation to improve human-computer interaction. Computational linguistics combines ambitious goals like full language understanding with realistic current applications.
Description of the subsystems of language and how teachers can draw on their knowledge of language and its subsystems to support ELs in their acquisition of language
Description of the subsystems of language and how teachers can draw on their knowledge of language and its subsystems to support ELs in their acquisition of language
This power point presentation was created by Myself using various references in internet (references are mentioned in slides to help you create your own) for the "partial fulfillment of Bachelors Degree of Computer Science and Information
Technology" from Tribhuvan University.
This power point presentation was created by Myself using various references in internet (references are mentioned in slides to help you create your own) for the "partial fulfillment of Bachelors Degree of Computer Science and Information
Technology" from Tribhuvan University.
This project was done when I was 2nd grade at guidance school as a 'very' simple game! :D
the game-play consists of shooting the flying birds, and if you miss them your weapon will decrease in level. The main bug of the game is that there's no rewards and the player will lose anyways!
"" 'save' the presentation then 'slide show' to view the project ""
Conversational AI Agents have become mainstream today due to significant advancements in the methods required to build accurate models, such as machine learning and deep learning, and, secondly, because they are seen as a natural fit in a wide range of domains, such as healthcare, e-commerce, customer service, tourism, and education, that rely heavily on natural language conversations in day-to-day operations. This rapid increase in demand has been matched by an equally rapid rate of research and development, with new products being introduced on a daily basis.
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EVALUATION OF CHATBOT TECHNOLOGY: THE CASE OF GREECEkevig
In recent years, the field of Artificial Intelligence has made significant strides, particularly in advancing
chatbots through Natural Language Processing (NLP) technology. Recently, however, there has been
intense competition in this industry, with major tech companies consistently introducing new and improved
solutions. Nevertheless, the Greek context introduces several unique challenges and obstacles to the
adoption of modern solutions, owing to the distinctiveness and relative rarity of the Greek language, as
well as the limited financial resources of the Greek economy. The objective of this study is to assess the
performance of chatbots in terms of the quality of their responses, including relevance, naturalness,
coherence, accuracy, and vocabulary, and to gauge user experience and satisfaction. An additional
objective is to acquire a comprehensive comparative overview of chatbot performance in Greece, both on a
per-question basis and when comparing related questions. The chosen method for evaluation is a guided
interview employing closed-type questions. The intention is to gather structured and quantified data in an
area where the typical internet user may not possess extensive familiarity or prior experience with such
evaluations. Conclusions were drawn for each question, enabling a focused and comparative assessment of
solution quality, identification of potential trends, and verification of response consistency.
Evaluation of Chatbot Technology: The Case of Greecekevig
In recent years, the field of Artificial Intelligence has made significant strides, particularly in advancing chatbots through Natural Language Processing (NLP) technology. Recently, however, there has been intense competition in this industry, with major tech companies consistently introducing new and improved solutions. Nevertheless, the Greek context introduces several unique challenges and obstacles to the adoption of modern solutions, owing to the distinctiveness and relative rarity of the Greek language, as well as the limited financial resources of the Greek economy. The objective of this study is to assess the performance of chatbots in terms of the quality of their responses, including relevance, naturalness, coherence, accuracy, and vocabulary, and to gauge user experience and satisfaction. An additional objective is to acquire a comprehensive comparative overview of chatbot performance in Greece, both on a per-question basis and when comparing related questions. The chosen method for evaluation is a guided interview employing closed-type questions. The intention is to gather structured and quantified data in an area where the typical internet user may not possess extensive familiarity or prior experience with such evaluations. Conclusions were drawn for each question, enabling a focused and comparative assessment of solution quality, identification of potential trends, and verification of response consistency.
NEW TRENDS IN LESS-RESOURCED LANGUAGE PROCESSING: CASE OF AMAZIGH LANGUAGEkevig
The coronavirus (COVID-19) pandemic has dramatically changed lifestyles in much of the world. It forced
people to profoundly review their relationships and interactions with digital technologies. Nevertheless,
people prefer using these technologies in their favorite languages.
New Trends in Less-Resourced Language Processing: Case of Amazigh Languagekevig
The coronavirus (COVID-19) pandemic has dramatically changed lifestyles in much of the world. It forced people to profoundly review their relationships and interactions with digital technologies. Nevertheless, people prefer using these technologies in their favorite languages. Unfortunately, most languages are considered even as low or less-resourced, and they do not have the potential to keep up with the new needs. Therefore, this study explores how this kind of languages, mainly the Amazigh, will behave in the wholly digital environment, and what to expect for new trends. Contrary to last decades, the research gap of low and less-resourced languages is continually reducing. Nonetheless, the literature review exploration unveils the need for innovative research to review their informatization roadmap, while rethinking, in a valuable way, people’s behaviors in this increasingly changing environment. Through this work, we will try first to introduce the technology access challenges, and explain how natural language processing contributes to their overcoming. Then, we will give an overview of existing studies and research related to under and less-resourced languages’ informatization, with an emphasis on the Amazigh language. After, based on these studies and the agile revolution, a new roadmap will be presented.
Demystifying Natural Language Processing: A Beginner’s Guidecyberprosocial
In today’s digital age, the realm of technology constantly pushes boundaries, paving the way for revolutionary advancements. Among these breakthroughs, one particularly fascinating field gaining momentum is Natural Language Processing (NLP). It refers to the ability of computers to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. This article aims to shed light on the intricacies of NLP, its applications, and its significance in various sectors.
PurposeSpeech recognition software has existed for decades; diff.docxmakdul
Purpose
Speech recognition software has existed for decades; different modifications have been made to the application to enable custom uses. The goal of this research is to create a program that will use speech recognition features to help speakers who have trouble with English word’s pronunciation to improve their speech pattern. The program will also help them to track their speech improvement progress and receive a feedback.
Project objectives
To help people with difficulties with English words improve their speech patterns
To help English language learners track their progress in speech improvement
Related Work
1. Speech recognition in assistive technology
Speech recognition is defined as the process through which human words are converted into a format that can be readable in a machine, for example, a computer or even a phone. Speech recognition technology which is also often referred to as computer speech recognition or the automatic speech recognition are software and devices which are used to convert words that are spoken into text(Ifukube, 2017). It works by an individual speaking into the microphone of the device which is connected to a machine or a sound detecting software, and then the sound is converted into numbers and to a readable text through algorithms. This assistive technology plays a very major role in improving speech patterns and more so in education as will be discussed below.
The first way through which speech recognition technologies can be used in assisting to improve the speech patterns is by allowing a greater level of interaction with disabled individuals. Physical disability can be a big barrier to communication between individuals; for example, it is impossible to have a conversation with an individual who does not have the hearing ability. Speech recognition helps to break such barrier and enhance speech and communication by for example by converting the spoken words into a readable text which the other individual can read and also respond. This technology can also help students who do not have motor skills such as the use of their hands or legs to still do the same tasks as the other. They can use the technology to make their reports and research and write just like any other student.
Second, the speech recognition technology has been very instrumental in improving speech patterns by improving the level of fluency of individuals. This is because the speech recognition software has evolved to a level where it has the ability to gauge the reading ability of individuals. Individuals can simply read into the machine, and it can be able to gauge their ability and tell what they are reading right and what they are reading wrong and gauge their fluency levels. An individual can very easily make use of this technology to enhance their reading abilities, their pronunciation and also to practice fluency.
Third, the speech recognition technology is very useful in improving speech patterns by enhancing language deve ...
The Rise Of ChatGPT_ Advancements In AI-Language Model Technology.pdfLucas Lagone
ChatGPT is the Most Recent AI language model technology that is taking the world by storm. Learn how it works, & potential impact on the future of language communication.
Original source: https://www.nevinainfotech.com/blog/advancements-in-ai-language-model-technology/
Artificial Intelligence has unleashed a wave of innovation, from effortlessly summarizing
articles to engaging in deep, thought-provoking conversations — with large language
models taking on the primary workload.
Enter the extraordinary realm of large language models (LLMs), the brainchild of deep
learning algorithms. These powerhouses not only decipher and grasp massive amounts
of data but also possess the uncanny ability to recognize, summarize, translate, predict,
and even generate a diverse range of textual and coding content.
XAI LANGUAGE TUTOR - A XAI-BASED LANGUAGE LEARNING CHATBOT USING ONTOLOGY AND...ijnlc
In this paper, we proposed a XAI-based Language Learning Chatbot (namely XAI Language Tutor) by using ontology and transfer learning techniques. To facilitate three levels of language learning, XAI Language Tutor consists of three levels for systematically English learning, which includes: 1) phonetics level for speech recognition and pronunciation correction; 2) semantic level for specific domain conversation, and 3) simulation of “free-style conversation” in English - the highest level of language chatbot communication as “free-style conversation agent”. In terms of academic contribution, we implement the ontology graph to explain the performance of free-style conversation, following the concept of XAI (Explainable Artificial Intelligence) to visualize the connections of neural network in bionics, and explain the output sentence from language model. From implementation perspective, our XAI Language Tutor agent integrated the mini-program in WeChat as front-end, and fine-tuned GPT-2 model of transfer learning as back-end to interpret the responses by ontology graph.
All of our source codes have uploaded to GitHub: https://github.com/p930203110/EnglishLanguageRobot
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. Computational linguistics (CL) is a discipline between linguistics and
computer science which is concerned with the computational aspects of the
human language faculty. It belongs to the cognitive sciences and overlaps
with the field of artificial intelligence (AI), a branch of computer
science aiming at computational models of human cognition. Computational
linguistics has applied and theoretical components.
4. Theoretical CL takes up issues in theoretical linguistics and cognitive science. It deals
with formal theories about the linguistic knowledge that a human needs for generating
and understanding language. Today these theories have reached a degree of
complexity that can only be managed by employing computers. Computational linguists
develop formal models simulating aspects of the human language faculty and
implement them as computer programs. These programs constitute the basis for the
evaluation and further development of the theories. In addition to linguistic
theories, findings from cognitive psychology play a major role in simulating linguistic
competence. Within psychology, it is mainly the area of psycholinguistics that
examines the cognitive processes constituting human language use. The relevance of
computational modeling for psycholinguistic research is reflected in the emergence of a
new sub discipline: computational psycholinguistics.
6. Applied CL focuses on the practical outcome of modeling human language use.
The methods, techniques, tools and applications in this area are often
subsumed under the term language engineering or (human) language
technology. Although existing CL systems are far from achieving human
ability, they have numerous possible applications. The goal is to create software
products that have some knowledge of human language. Such products are
going to change our lives. They are urgently needed for improving humanmachine interaction since the main obstacle in the interaction between human
and computer is a communication problem. Today's computers do not
understand our language but computer languages are difficult to learn and do
not correspond to the structure of human thought. Even if the language the
machine understands and its domain of discourse are very restricted, the use of
human language can increase the acceptance of software and the productivity
of its users.
8. Natural language interfaces enable the user to communicate with the computer
in French, English, German, or another human language. Some applications of
such interfaces are database queries, information retrieval from texts, so-called
expert systems, and robot control. Current advances in the recognition of
spoken language improve the usability of many types of natural language
systems. Communication with computers using spoken language will have a
lasting impact upon the work environment, completely new areas of application
for information technology will open up. However, spoken language needs to be
combined with other modes of communication such as pointing with mouse or
finger. If such multimodal communication is finally embedded in an effective
general model of cooperation, we have succeeded in turning the machine into a
partner.
10. Much older than communication problems between human beings and
machines are those between people with different mother tongues. One of the
original aims of applied computational linguistics has always been fully
automatic translation between human languages. From bitter experience
scientists have realized that they are still far away from achieving the ambitious
goal of translating unrestricted texts. Nevertheless computational linguists
have created software systems that simplify the work of human translators and
clearly improve their productivity. Less than perfect automatic translations can
also be of great help to information seekers who have to search through large
amounts of texts in foreign languages.
12. The rapid growth of the Internet/WWW and the emergence of the information
society poses exciting new challenges to language technology. Although the
new media combine text, graphics, sound and movies, the whole world of
multimedia information can only be structured, indexed and navigated through
language. For browsing, navigating, filtering and processing the information on
the web, we need software that can get at the contents of documents.
Language technology for content management is a necessary precondition for
turning the wealth of digital information into collective knowledge. The
increasing multilingualism of the web constitutes an additional challenge for our
discipline. The global web can only be mastered with the help of multilingual
tools for indexing and navigating. Systems for cross lingual information and
knowledge management will surmount language barriers for ecommerce, education and international cooperation.
14. We still do not know very well how people produce and comprehend
language. Yet our understanding of the intricate mechanisms that underlay
human language processing keeps growing. Modeling such mechanisms on a
computer also helps us to discover and formally describe hidden properties of
human language that are relevant for any kind of language processing
including many useful software applications. Our long term goal is the deep
understanding of human language and powerful intelligent linguistic
applications. However, even today's language technologies full of clever short
cuts and shallow processing techniques can be turned into badly needed
software products.
16. For many students and practitioners of computational linguistics the special
attraction of the discipline is the combination of expertise from the
humanities, natural and behavioral sciences, and engineering. Scientific
approaches and practical techniques come from linguistics, computer
science, psychology, and mathematics. At some universities the subject is
taught in computer science at others it belongs to linguistics or cognitive
science. In addition there is a small but growing number of programs and
departments dedicated solely to computational linguistics.