A multimodal pattern recognition framework for speaker detection
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Communication between humans deeply relies on the capability of expressing and recognizing feelings. For this reason, research on human-machine interaction needs to focus on the recognition and simulation of emotional states, prerequisite of which is the c ...
Supply chains (SC) are complex systems in which human beings play a key role. Whereas human impact is often taken into account in simulation models in terms of physical flows (material handling, fabrication), it is far less the case in terms of information ...
In this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, where the object instances are 1-D short-time spectral vectors obtained from the speech signal. More precisely, we investigate the ge ...
Activity and context recognition in pervasive and wearable computing ought to continuously adapt to changes typical of open-ended scenarios, such as changing users, sensor characteristics, user expectations, or user motor patterns due to learning or aging. ...
Recent years have seen an increasing interest in sparseness constraints for image classification and object recognition, probably motivated by the evidence of sparse representations internal in the primate visual cortex. It is still unclear, however, whethe ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM-based algorithm, capable of learning model representations incrementally while keeping under c ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM- -based algorithm, capable of learning model representations incrementally while keeping under ...
Most state-of-the-art approaches to action recognition rely on global representations either by concatenating local information in a long descriptor vector or by computing a single location independent histogram. This limits their performance in presence o ...
With the increasing demand of information for more immersive applications such as Google Street view or 3D movies, the efficient analysis of visual data from cameras has gained more importance. This visual information permits to extract some crucial inform ...
A semi-distributed hydrological model was developed for the upper Rhone River basin in Switzerland to provide 72 h lead time discharge forecasts for the optimization of a multireservoir system during floods The performance of the model is presented and cor ...