An Evaluation Framework for Multimodal Interaction, Ina Wechsung
Автор: Ina Wechsung Название: An Evaluation Framework for Multimodal Interaction ISBN: 3319038095 ISBN-13(EAN): 9783319038094 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Exhaustive and empirically validated, this taxonomy of qualitative aspects of multimodal interaction includes an evaluative questionnaire, a breakdown of factors influencing modality choice, models for comparing perceived and actual quality, and much more.
Описание: Active Shape Model Vs. Deep Learning for Facial Emotion Recognition in Security.- Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes.- Human Mobility-Pattern Discovery and Next-Place Prediction from GPS data.- Fusion Architectures for Multimodal Cognitive Load Recognition.- Face Recognition in Home Security System Using Tensor Decomposition Based on Radix Hierarchical SVD.- Performance analysis of gesture recognition classifiers for building a human robot interface.- On Automatic Question Answering Using Efficient Primal-dual Models.- Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action Recognition.- Audio Visual Speech Recognition Using Deep Recurrent Neural Networks.- Audio-Visual Recognition of Pain Intensity.- The Sense Emotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System.- Photometric Stereo for 3D face reconstruction using non linear illumination models.- Recursively Measured Action Units.
Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014.
Annotating the TCD D-ANS Corpus - A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.- Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.- A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.-Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.
Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the First IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction (MPRSS2012), held in Tsukuba, Japan in November 2012, in collaboration with the NLGD Festival of Games.
Автор: Andrei Popescu-Belis; Rainer Stiefelhagen Название: Machine Learning for Multimodal Interaction ISBN: 3540858520 ISBN-13(EAN): 9783540858522 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2008, held in Utrecht, The Netherlands, in September 2008. This title features papers that cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction.
Описание: The improvement affects the prediction of dialogue metrics that are related to dialogue efficiency and dialogue effectiveness.Furthermore, the book describes a parameter-based data model, as well as a related framework.
Описание: This book constitutes the refereed proceedings of the 5th International Conference of the CLEF Initiative, CLEF 2014, held in Sheffield, UK, in September 2014.
Автор: John N.A Brown; Anton Josef Fercher; Gerhard Leitn Название: Building an Intuitive Multimodal Interface for a Smart Home ISBN: 3319565311 ISBN-13(EAN): 9783319565316 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes an innovative approach to the interaction between humans and a smart environment; This book describes the efforts, undertaken over several years, to design, implement, and test a model of interaction that allows untrained individuals to intuitively control a complex series of networked and embedded systems.
Описание: This thesis covers various facets of brain image computing methods and illustrates the scientific understanding of neurodegenerative disorders based on four general aspects of multimodal neuroimaging computing: neuroimaging data pre-processing, brain feature modeling, pathological pattern analysis, and translational model development.
Автор: Jaeyoung Choi; Gerald Friedland Название: Multimodal Location Estimation of Videos and Images ISBN: 3319098608 ISBN-13(EAN): 9783319098609 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents an overview of the field of multimodal location estimation. The book describes fundamental methods of acoustic, visual, textual, social graph, and metadata processing as well as multimodal integration methods used for location estimation.
Автор: Chen Название: Robust Multimodal Cognitive Load Measurement ISBN: 3319316982 ISBN-13(EAN): 9783319316987 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Поставка под заказ.
Описание: This book explores robust multimodal cognitiveload measurement with physiological and behavioural modalities, which involve theeye, Galvanic Skin Response, speech, language, pen input, mouse movement andmultimodality fusions. Factors including stress, trust, and environmentalfactors such as illumination are discussed regarding their implications forcognitive load measurement. Furthermore, dynamic workload adjustment andreal-time cognitive load measurement with data streaming are presented in orderto make cognitive load measurement accessible by more widespread applicationsand users. Finally, application examples are reviewed demonstrating thefeasibility of multimodal cognitive load measurement in practical applications.This is thefirst book of its kind to systematically introduce various computationalmethods for automatic and real-time cognitive load measurement and by doing somoves the practical application of cognitive load measurement from the domainof the computer scientist and psychologist to more general end-users, ready forwidespread implementation.Robust Multimodal CognitiveLoad Measurement is intended for researchers and practitioners involved with cognitiveload studies and communities within the computer, cognitive, and socialsciences. The book will especially benefit researchers in areas like behaviouranalysis, social analytics, human-computer interaction (HCI), intelligentinformation processing, and decision support systems.
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