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In this chapter we discuss multimodal interface technology. We present examples of multimodal interfaces and show problems and opportunities. Fusion of modalities is discussed and some roadmap discussions on research in mul-timodality are summarized. This chapter also discusses future developments where, rather than communicating with a single computer, users communicate with their environment using...
For a Personal Video Recorder (PVR) to provide an enriched TV experience to the user, personalization, achieved via a recommender engine, is the key. One of the thorny problems facing a recommender system is that of a cold start: how does one capture the user preferences quickly and effectively and provide user-specific personalization? To address the cold start problem, we propose a stereotype-enabled...
Query by humming is an interaction concept in which the identity of a melody has to be revealed fast and orderly from a given sung input using a large database of known melodies. In short, it tries to detect the pitches in a sung melody and compares these pitches with symbolic representations of the known melodies. Melodies that are similar to the sung pitches are retrieved. Approximate pattern matching...
Summarization and abstraction are our survival tools in this age of information explosion and availability. Ability to summarize will be seen as essential part of intelligent behavior of the consumer devices. We introduce the notion of video summarization, and provide definitions of the different flavors of summaries: Video skim, highlights, and structured multimedia summary. We present different...
Four audio feature sets are evaluated in their ability to differentiate five audio classes: popular music, classical music, speech, background noise and crowd noise. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and two new sets based on perceptual models of hearing. The temporal behavior of the features is analyzed and parameterized and these parameters...
Multimedia content in the form of non-textual data is becoming more and more abundant. This chapter addresses the problem of adequate natural and efficient access to this increasing amount of available content, sometimes referred to as the content bottleneck. We focus on the special case of spoken audio content and demonstrate how partly erroneous document information (e.g. from automatic speech recognizer...
Machine learning deals with programs that learn from experience, i.e. programs that improve or adapt their performance on a certain task or group of tasks over time. In this tutorial, we outline some issues in machine learning that pertain to ambient and computational intelligence. As an example, we consider programs that are faced with the learning of tasks or concepts which are impossible to learn...
An important aspect of Ambient Intelligence is a convenient user interface, supporting several user-friendly input modalities. Speech is one of the most natural modalities for man-machine interaction. Numerous applications in the context of Ambient Intelligence — whether referring to a single input modality or combining different ones — involve some pattern classification task. Experience shows that...
This chapter presents two approaches how to automatically find useful phrases that extract semantic meaning from user utterances in natural language dialogue applications. The presented algorithms are based on exchange clustering with a word-error like criterion and on the expectation-maximization algorithm, respectively, and work on annotated training texts. The methods are applied to the Philips...
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