302,945 research outputs found

    Natural Language Processing: The Future of Content Generation and It's Applications

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    Natural Language Processing (NLP) is a field of artificial intelligence and computer science that deals with the interaction between computers and humans in the form of natural language. It involves using algorithms and statistical models to analyze, generate, and understand human language, enabling computers to interpret and respond to human requests naturally and intelligently

    Natural Language Processing for Enterprise Applications

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    Researchers are concentrating on more efficient communication technologies that can emulate human interactions and comprehend natural languages and human emotions as a result of people's growing reliance on computer-assisted systems. Unstructured data, which is deemed useless, has increased due to the issue of information overload in every industry, including business, healthcare, education, etc. In this context, natural language processing (NLP) is one of the efficient technologies that may be used with more sophisticated technologies, such as machine learning, artificial intelligence, and deep learning, to enhance the interpretation and processing of natural language. In addition to improving human-computer interaction, this can also enable massive amounts of useless and unstructured data to be analyzed and formatted in numerous industrial applications. This will produce significant results that can improve decision-making and hence increase operational effectiveness. This chapter introduces the idea of NLP, its background, and its current state while also going through examples of its use in various industrial fields. Keywords: Natural Language Processing, Artificial Intelligence, Machine Learning

    Some Aspects Regarding Natural Language Processing

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    It is known that the key properties of every computer system interface is to be very friendly. What is more natural than a communication between human and machine realized in natural language? Natural language is a medium for human-machine interaction that has several obvious and desirable properties: it provides a means of accessing information in the computer independently of its structure and encodings, it shields the user from the formal access language of the underlying system and it is available with a minimum of training. There are many approaches regarding natural language processing but in this study, I focus my attention to DCG grammar, and shortly, ATN grammar. I have tried to present the main analysis that must be performed while processing a text: syntactic analysis, morphologic analysis, semantic analysis and pragmatic analysis.grammar, analysis, syntactic, morphologic, semantic, pragmatic.

    Advanced HCI and 3D Web over Low performance Devices

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    This position paper presents the authors’ goals on advanced human computer interaction and 3D Web -- Previous work on speech, natural language processing and visual technologies has achieved the development of the BerbaTek language learning demonstrator, a 3D virtual tutor that supports Basque language students through spoken interaction -- Next steps consist on migrating all the system to multidevice web technologies -- This paper shows the architecture defined and the steps to be performed in the next month

    Computational Intelligence and Human- Computer Interaction: Modern Methods and Applications

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    The present book contains all of the articles that were accepted and published in the Special Issue of MDPI’s journal Mathematics titled "Computational Intelligence and Human–Computer Interaction: Modern Methods and Applications". This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human–computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this book will be interesting and useful for those working in various areas of artificial intelligence, human–computer interaction, and software engineering as well as for those who are interested in how these domains are connected in real-life situations

    I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions

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    By utilizing different communication channels, such as verbal language, gestures or facial expressions, virtually embodied interactive humans hold a unique potential to bridge the gap between human-computer interaction and actual interhuman communication. The use of virtual humans is consequently becoming increasingly popular in a wide range of areas where such a natural communication might be beneficial, including entertainment, education, mental health research and beyond. Behind this development lies a series of technological advances in a multitude of disciplines, most notably natural language processing, computer vision, and speech synthesis. In this paper we discuss a Virtual Human Journalist, a project employing a number of novel solutions from these disciplines with the goal to demonstrate their viability by producing a humanoid conversational agent capable of naturally eliciting and reacting to information from a human user. A set of qualitative and quantitative evaluation sessions demonstrated the technical feasibility of the system whilst uncovering a number of deficits in its capacity to engage users in a way that would be perceived as natural and emotionally engaging. We argue that naturalness should not always be seen as a desirable goal and suggest that deliberately suppressing the naturalness of virtual human interactions, such as by altering its personality cues, might in some cases yield more desirable results.Comment: eNTERFACE16 proceeding

    Extraction of Word Set for Increasing Human-Computer Interaction in Information Retrieval

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    We present a mechanism that provides word sets which can make human-computer interaction more active in the course of information retrieval, with natural language processing technology and a mathematic measure for calculating degree of inclusion. We show what type of words should be added to the current query, i.e. keywords which previously had been input, in order to make human-computer interaction more creative. We try to extract related word sets with taxonomical and non-taxonomical relations from documents by employing case-marking particles derived from syntactic analysis. Then, we verify which kind of related words is more useful as an additional word for retrieval support and makes human-computer interaction more fruitful

    Natural Language Processing Applications in Business

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    Increasing dependency of humans on computer-assisted systems has led to researchers focusing on more effective communication technologies that can mimic human interactions as well as understand natural languages and human emotions. The problem of information overload in every sector, including business, healthcare, education etc., has led to an increase in unstructured data, which is considered not to be useful. Natural language processing (NLP) in this context is one of the effective technologies that can be integrated with advanced technologies, such as machine learning, artificial intelligence, and deep learning, to improve the process of understanding and processing the natural language. This can enable human-computer interaction in a more effective way as well as allow for the analysis and formatting of large volumes of unusable and unstructured data/text in various industries. This will deliver meaningful outcomes that can enhance decision-making and thus improve operational efficiency. Focusing on this aspect, this chapter explains the concept of NLP, its history and development, while also reviewing its application in various industrial sectors
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