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检索条件"任意字段=8th IFIP International Conference on Engineering for Human-Computer Interaction"

共 2051 条记录，以下是311-320 订阅

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human-Centered Software engineering for Changing Contexts of Use ifip WG 13.2 Workshop at INTERACT 2021 18th

Human-Centered Software Engineering for Changing Contexts of...

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18th ifip TC 13 international conference on human-computer interaction (INTERACT)

作者： Sauer, Stefan Bernhaupt, Regina Ardito, Carmelo Paderborn Univ Paderborn Germany Eindhoven Univ Technol Eindhoven Netherlands Politecn Bari Bari Italy

ISBN: (纸本)9783030856076;9783030856069

the context of use plays an important role in human-Centered Software engineering (HCSE). Typically, user, environment, and platform are considered to make up the core aspects of the context of use. Changing the context of use has significant impact on how to design and develop with a user-centered perspective and how usage of these systems changed for example in the current pandemic situation with a focus on remote work. New kinds of work environments in industry providing different types of user assistance evolve, new settings for remote and distributed work styles are required to account for social distancing, or the trends towards autonomous and AI-based systems demand for new ways of thinking about socio-technical interaction and systems. this workshop promotes sharing of knowledge and experiences that address how to deal with evolving contexts of use in today's and future application domains and its influence on human-centered socio-technical system design and development practices. Beyond the traditional themes of ifip Working Group 13.2 workshops, the main focus lies on theories, methods, and approaches for dealing with the context of use, its influence on HCSE, and factors for its change over time.

关键词： human-Centered Software engineering Context of use Change Adaptive user interfaces

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Enhanced Multimodal Conversational AI Using Speech and Image Integration 5th

Enhanced Multimodal Conversational AI Using Speech and Image...

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5th international conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Dixit, Deepali Tyagi, Mihul Kandoi, Raunak Singh, Raghuraj School of Engineering and Technology Sharda University Greater Noida201310 India

ISBN: (纸本)9789819773701

the development of conversational artificial intelligence (AI) is examined in this research paper, with a focus on how speech and image recognition technologies can be combined to transform and interact with systems. the emphasis is on cutting-edge developments in multimodal conversational AI, particularly the smooth fusion of sophisticated image and speech processing methods to improve user experiences. the study addresses the applications, difficulties and potential applications of multimodal conversational AI by conducting a thorough review of the existing literature and case studies. By emphasizing the significance of enhancing voice recognition algorithms and utilizing advanced image processing techniques, the study promotes contextual understanding and customization. We have developed an innovative multimodal conversational AI system that integrates speech, text and image processing capabilities for seamless human–computer interactions. this study presents an improved multimodal conversational AI system that integrates several techniques, such as Google Text-to-Speech (gtts), speech recognition, sound playback and Convolutional Neural Networks (CNN). Our model architecture combines RNNs for sequential data analysis, CNNs for image processing and attention mechanisms for context extraction. Trained on diverse datasets, our model is optimized for accuracy and robustness. Evaluation against existing models demonstrates superior performance in terms of accuracy, speed and resource efficiency. Our study highlights how improved multimodal conversational AI can advance the field of human–computer interaction. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Recognizing human-object interactions for a Home Assistive Robot

Recognizing Human-object Interactions for a Home Assistive R...

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Automation, Control and Robotics engineering (CACRE), international conference on

作者： Liangliang Wang Guanglei Huo Xinwei Chen Chengxi Huang School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China Fujian(Quanzhou)-HIT Research Institute of Engineering and Technology Quanzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

To enable robots to understand a specific assistive task during human-robot interactions under complex home scenes, at the center is the problem of human-object interaction (HOI) recognition. In particular, aiming at identifying efficiently, this paper proposes a graph convolutional network (GCN) by considering the similarity and proximity of human and object nodes, based on which the geometric positions and morphological relationships are explored. Also, a supplementary convolutional neural network (CNN) is fused to GCN to extract the global semantic features, which also ensures the recognition applicability for the cases where detectors fall into failure. Experiments on V-COCO demonstrate our approach, and results in real-world scenes on our assistive robot – Xiaozhi II verify its robustness.

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A Review of Sign Language Systems 16

A Review of Sign Language Systems

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16th international conference on Developments in eSystems engineering, DeSE 2023

作者： Moradi, Marzieh Kannan, Deepika Dhanabalan Asadianfam, Shiva Kolivand, Hoshang Aldhaibani, Omar King's Leadership Academy Liverpool Dingle Vale LiverpoolL8 9SJ United Kingdom Liverpool John Moores University Liverpool School of Computer Science and Maths LiverpoolL3 3AF United Kingdom Liverpool John Moores University Liverpool LiverpoolL3 3AF United Kingdom Qom University of Technology Faculty of Electrical & Computer Engineering Qom Iran Islamic Azad University Qom Branch Department of Computer Engineering Qom Iran Liverpool John Moores University Liverpool Department of Computer Science LiverpoolL3 3AF United Kingdom Staffordshire University School of Computing and Digital Technologies United Kingdom

ISBN: (纸本)9798350381344

Sign languages are languages that utilize the visual-manual modality to convey meaning. these languages are expressed through manual articulations combined with non-manual elements. Sign languages are complete natural languages, possessing their own grammar and lexicon. they are primarily used by individuals who are Deaf or have hearing impairments. Sign languages are not universal and are not mutually intelligible with one another, though they do exhibit striking similarities among them. In the context of Britain, the most prevalent form of Sign Language is known as British Sign Language (BSL). BSL possesses its own distinct grammatical structure and syntax;as a language, it is neither dependent on nor closely related to spoken English. this paper offers a comprehensive review of sign language systems, including an exploration of related studies on British Sign Language, as well as an examination of the legal, social, and ethical considerations associated with these languages. © 2023 IEEE.

关键词： human computer interaction

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Immersion and Presence in Virtual Reality Applications for Physical therapy and Upper Limb Rehabilitation 15th

Immersion and Presence in Virtual Reality Applications for P...

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15th international conference on Social Computing and Social Media, SCSM 2023, held as part of the 25th international conference on human-computer interaction, HCII 2023

作者： Fayed, Mohamed Almadi, Faisal Almadi, Meteb Almudawah, Rayan Taha Alotaibi, Faisal Adam, Abdullah Aldubaib, Faisal Alshaikh, Alya Alhamad, Layan ElSayed, Hoda Software Engineering Department Alfaisal University Riyadh Saudi Arabia UpDown Game Studio Riyadh Saudi Arabia Game Innovation Lab College of Engineering Riyadh Saudi Arabia

ISBN: (纸本)9783031359262

human factors in the design of physical therapy virtual reality (VR) applications are important to consider in the creation of high-fidelity applications. the human factors contributing to the design concepts of immersion and presence in VR are inadequately understood. the aim of this study is to introduce a novel framework to design for immersion and presence in VR applications in the context of physical therapy in the virtual realm. the framework includes the dimension of self-embodiment for presence and realism for immersion. We present a use case of upper-limb therapy to demonstrate the framework’s utility in the design process of a gamified VR physical rehabilitation application. Design implications are discussed. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtual reality

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A Proposed Architecture of Mobile Service Provider Based Interactive Systems

A Proposed Architecture of Mobile Service Provider Based Int...

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international conference for Convergence of Technology (I2CT)

作者： Chandni Magoo Manjeet Singh Department of Computer Science and Engineering J.C. Bose University of Science and Technology Manav Rachna University Faridabad Department of Computer Science and Technology Manav Rachna University Faridabad

Chatbots are basically designed to imitate any human interaction to automate interaction and support. Numerous benefits of chatbots has led to its increased usage by different organizations to provide essential assistance to its various customers. the current interactive systems are mainly developed from two main concepts namely NLP and Machine Learning. Despite of this, there are certain challenges and limitations of current chatbots. In this paper we will review some of the current chatbots with their limitations and highlight some of the errors identified through survey analysis of different chatbots of some companies like Airtel, Vodafone and Jio etc. A survey is done to analyze the chatbots on various metrics.

关键词： Surveys Measurement Interactive systems Atmospheric modeling Oral communication Machine learning Companies

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Deep learning for speech emotion recognition: a technical tutorial on the state of the art

Deep learning for speech emotion recognition: a technical tu...

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international conference on Information Systems engineering (ICISE)

作者： Hai Liu Jiawen Li Li Zhao Junya Si Weixin Li Dazhen Shen Zixin Li Tingting Liu School of Computer Science Wuhan Donghu University Wuhan China

Speech is the simplest, most natural and most direct way of communication between people, and the rise of smart devices makes speech emotion recognition (SER) technology the most important part of human-computer interaction (HCI). this paper will start from the concept of language emotion recognition, and research the systematic research on speech emotion recognition in five aspects. First, we review the classification of some phonetic emotional features. Secondly, we introduce some of the latest technologies for speech emotion recognition based on traditional and machine learning. Furthermore, we summarize the classification of some common datasets. Finally, we discuss the practical application and future research direction of speech emotion recognition.

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Exploration and Optimization Technique for Speech Enhancement and Emotion Recognition Using Deep Neural Network 8

Exploration and Optimization Technique for Speech Enhancemen...

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8th international conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Dere, Yash Botre, Prasad Telgar, Audumbar Paikrao, Pavan Kumar D. Dr D Y Patil Institute of Technology Electronics and Telecommunication Engineering Pune India

ISBN: (纸本)9798331520762

One of the most fascinating and difficult tasks in human-computer interaction is speech emotion recognition. the practice of attempting to determine the types of affective and emotional states in speech is known as speech emotion recognition. this takes advantage of the fact that voice pitch and tone often reveal underlying emotion. Animals like horses and dogs also use this phenomenon to understand human emotion. We attempted to identify emotion in a brief voice communication in this experiment. Four datasets-SAVEE, CREMAD, IEMOCAP, TESS, and RAVDESS-that comprise about seven primary emotion types-Happy, Fear, Angry, Disgust, Surprised, Sad, or Neutral-were employed in this effort. In contrast to earlier research, where each researcher worked on a different dataset, our project integrated the four datasets-SAVEE, RAVDESS, TESS, and CREMA-D into a single file, which we then sent as input to the model in the form of a wav file. After removing the noise from the data using feature extraction techniques (MFCC, ZCR, and RMSE), we organized the sequential data in a 3D array format that the CNN model can use. the average accuracy of the model is 76% during the testing phase and 87% during the training phase, according to our repeated testing with different values after putting the data into a graphical format using the Matplotlib tool. © 2025 IEEE.

关键词： Deep neural networks

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Real Time Virtual Yoga Tutor

Real Time Virtual Yoga Tutor

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international conference for Convergence of Technology (I2CT)

作者： Anuradha M Adithya Rao Shreyas S Sanjaya K C ECE Department PES University Bangalore India Electronics and Communications Engineering PES University Bangalore India

Articulated pose estimation in computer vision is the field of research that deals with the development of algorithms and systems that can determine the position and orientation of an articulated body, such as a human body, in 3D space. It has a wide range of applications, including motion capture, human-computer interaction, and robotics. In the context of the project, the goal is to estimate the position of human body parts and joints in each image, using a pre-trained pose estimation model, MediaPipe. the data obtained from this model is then used to explore various applications, with the focus being on building a yoga monitoring system. the system analyzes and tracks the user’s movements and postures, identifying any errors in their yoga routine. this allows the system to provide real-time feedback to the user, pointing out any inaccuracies in their body pose, so they can correct their mistakes.

关键词： computer vision three-dimensional displays Webcams Tracking Biological system modeling Pose estimation Real-time systems

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Swarm Intelligence-Based Feature Selection Algorithm of EEG Classification for Brain Emotion Detection: A Review

Swarm Intelligence-Based Feature Selection Algorithm of EEG ...

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international conference for Convergence of Technology (I2CT)

作者： Gaganjot Kaur Meenu Gupta Rakesh Kumar Department of Computer Science and Engineering Chandigarh University Punjab India

In recent technology, Brain computer Interfacing (BCI) plays a prominent role through which a human can interact with the outside world using brain signals. Brain signals are the current reactions in the brain when neurological activity occurs and are closely associated with critical thinking, logical decision-making, recognition, human interaction, and to some extent, human Intelligence. Brain waves influence most real human body reactions; compared to other types of emotion analysis, brain wave emotion analysis comes out on top. Emotion Detection has a broad perspective in interdisciplinary research for neurologists, psychologists, engineers, etc. this paper aims to represent the latest comprehensive review of emotion detection techniques using Electroencephalography (EEG) Signals, feature extraction, feature selection, and classification, along with pointing out existing problems in the field and potential growth areas.

关键词： Emotion recognition Electric potential human intelligence Decision making Psychology Feature extraction Electroencephalography

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