280 research outputs found
Spoken content retrieval: A survey of techniques and technologies
Speech media, that is, digital audio and video containing spoken content, has blossomed in recent years. Large collections are accruing on the Internet as well as in private and enterprise settings. This growth has motivated extensive research on techniques and technologies that facilitate reliable indexing and retrieval. Spoken content retrieval (SCR) requires the combination of audio and speech processing technologies with methods from information retrieval (IR). SCR research initially investigated planned speech structured in document-like units, but has subsequently shifted focus to more informal spoken content produced spontaneously, outside of the studio and in conversational settings. This survey provides an overview of the field of SCR encompassing component technologies, the relationship of SCR to text IR and automatic speech recognition and user interaction issues. It is aimed at researchers with backgrounds in speech technology or IR who are seeking deeper insight on how these fields are integrated to support research and development, thus addressing the core challenges of SCR
Multimodålis ember-gép kapcsolatok
A multimodĂĄlis ember-gĂ©pkapcsolatok bemutatĂĄsa, jelentĆsĂ©ge. Az informatika Ă©s azon belĂŒl az interfĂ©sz fejlesztĂ©sek lehetĆsĂ©gei. PĂ©ldarendszerek, majd a Debreceni Egyetem sakkozĂłgĂ©pĂ©nek bemutatĂĄsa. A sakkozĂłgĂ©ppel vĂ©gzett humĂĄnteszt cĂ©lkitƱzĂ©se, statisztikai igazolĂĄsa.M
Human-Computer Interaction
In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools
SHELDON Smart habitat for the elderly.
An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare
Implicit image annotation by using gaze analysis
PhDThanks to the advances in technology, people are storing a massive amount of visual information in the online databases. Today it is normal for a person to take a photo of an event with their smartphone and effortlessly upload it to a host domain. For later quick access, this enormous amount of data needs to be indexed by providing metadata for their content. The challenge is to provide suitable captions for the semantics of the visual content. This thesis investigates the possibility of extracting and using the valuable information stored inside humanâs eye movements when interacting with digital visual content in order to provide information for image annotation implicitly. A non-intrusive framework is developed which is capable of inferring gaze movements to classify the visited images by a user into two classes when the user is searching for a Target Concept (TC) in the images. The first class is formed of the images that contain the TC and it is called the TC+ class and the second class is formed of the images that do not contain the TC and it is called the TC- class. By analysing the eye-movements only, the developed framework was able to identify over 65% of the images that the subject users were searching for with the accuracy over 75%. This thesis shows that the existing information in gaze patterns can be employed to improve the machineâs judgement of image content by assessment of human attention to the objects inside virtual environments.European Commission funded Network of Excellence PetaMedi
Natural language and spatial reasoning
Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 109-112).Making systems that understand language has long been a dream of artificial intelligence. This thesis develops a model for understanding language about space and movement in realistic situations. The system understands language from two real-world domains: finding video clips that match a spatial language description such as "People walking through the kitchen and then going to the dining room" and following natural language commands such as "Go down the hall towards the fireplace in the living room." Understanding spatial language expressions is a challenging problem because linguistic expressions, themselves complex and ambiguous, must be connected to real-world objects and events. The system bridges the gap between language and the world by modeling the meaning of spatial language expressions hierarchically, first capturing the semantics of spatial prepositions, and then composing these meanings into higher level structures. Corpus-based evaluations of how well the system performs in different, realistic domains show that the system effectively and robustly understands spatial language expressions.by Stefanie Anne Tellex.Ph.D
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