Signal Processing

This task evaluates performance of the sound event detection systems in multisource conditions similar to our everyday life, where the sound sources are rarely heard in isolation. Contrary to task 2, there is no control over the number of overlapping sound events at each time, not in the training nor in the testing audio data.

  • Signal Processing
  • Analog signal processing
  • Last Updated On: 
    Tue, 01/10/2017 - 15:56
    Citation Author(s): 
    Annamaria Mesaros, Toni Heittola, and Tuomas Virtanen

    The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Enea Cippitelli, Ennio Gambi, Samuele Gasparrini, Susanna Spinsante

    The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Enea Cippitelli, Ennio Gambi, Samuele Gasparrini, Susanna Spinsante

    The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the execution of the timed up and go test.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Enea Cippitelli, Ennio Gambi, Samuele Gasparrini, Susanna Spinsante

    The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the simulation of ADLs and falls.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Enea Cippitelli, Ennio Gambi, Samuele Gasparrini, Susanna Spinsante

    The dataset contains depth frames collected using Microsoft Kinect v1 in top-view configuration and can be used for fall detection.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Enea Cippitelli, Ennio Gambi, Samuele Gasparrini, Susanna Spinsante

    At the intersection of signal processing and information forensics, the Signal Processing Cup 2016 global competition has explored a time-varying location-dependent signature of power grids that can be intrinsically captured in media recordings. This signature is called the Electric Network Frequency (ENF) signals. Throughout the SP Cup 2016 competition, participants were provided with multiple training, practice, and testing datasets that consisted of recordings made in different grids and containing ENF traces.

  • Signal Processing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Adi Hajj-Ahmad, Chau-Wai Wong, and Min Wu

    Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room.

  • Signal Processing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    J. Eaton, A. H. Moore, N. D. Gaubitch, and P. A. Naylor

    Pages