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The combination of coordinated multi-point (CoMP) and underlay spectrum sharing promises substantial spectral efficiency (SE) gains for future cellular networks. However, this concept has been largely overlooked in the literature. Moreover, none of the few relevant studies consider the use of “standard” transmission strategies to facilitate the adoption of the aforementioned communication paradigm by 5G networks.

The combination of coordinated multi-point (CoMP) and underlay spectrum sharing promises substantial spectral efficiency (SE) gains for future cellular networks. However, this concept has been largely overlooked in the literature. Moreover, none of the few relevant studies consider the use of “standard” transmission strategies to facilitate the adoption of the aforementioned communication paradigm by 5G networks.

This paper shows that time varying pitch properties can be used advantageously within the segmentation step of a multi-talker diarization system. First a study is conducted to verify that changes in pitch are strong indicators of changes in the speaker. It is then highlighted that an individual’s pitch is smoothly varying and, therefore, can be predicted by means of a Kalman filter. Subsequently it is shown that if the pitch is not predictable then this is most likely due to a change in the speaker.

Neuromorphic vision sensing (NVS) hardware is now gaining traction as a low-power/high-speed visual sensing technology that circumvents the limitations of conventional active pixel sensing (APS) cameras. While object detection and tracking models have been investigated in conjunction with NVS, there is currently little work on NVS for higher-level semantic tasks, such as action recognition.

The task of Language-Based Image Editing (LBIE) aims at generating a target image by editing the source image based on the given language description. The main challenge of LBIE is to disentangle the semantics in image and text and then combine them to generate realistic images. Therefore, the editing performance is heavily dependent on the learned representation.

Audiovisual media are increasingly used to study the communication and behavior of animal groups, e.g. by placing microphones in the animals habitat resulting in huge datasets with only a small amount of animal interactions. The Orcalab has recorded orca whales since 1973 using stationary underwater hydrophones and made it publicly available on the Orchive. There exist over 15 000 manually extracted orca/noise annotations and about 20 000 h unseen audio data. To analyze the behavior and communication of killer whales we need to interpret the different call types.

Slide of Presentation in ICASSP 2019

This work deals with efficient atom selection procedure in
a continuous dictionary, as required for instance in a Frank-
Wolfe approach within a BLASSO problem for the onedimensional
deconvolution problem. We show that efficient
maximization of a correlation between any given vector and
an atom sweeping a continuous dictionary can be performed
through a particular piece-wise linear approximation of dictionaries:
the polar approximation. We finally identify the
polar approximation as being optimal in a mean square error

Speech-related Brain Computer Interfaces (BCI) aim primarily at finding an alternative vocal communication pathway for
people with speaking disabilities. As a step towards full decoding of imagined speech from active thoughts, we present a
BCI system for subject-independent classification of phonological categories exploiting a novel deep learning based