SPCN-L1.2
MACHINE LEARNING-BASED SOURCE-MATCHED CHANNEL CODING FOR SPEECH TRANSMISSION
Oemer Karakas, Andreas Brendel, Marco Breiling, Guillaume Fuchs, Sahana Raghunandan, Fraunhofer IIS, Germany; Wolfgang Gerstacker, FAU Erlangen-Nuernberg, Germany
Session:
SPCN-L1: Machine Learning for Communications Lecture
Track:
SPCN - Signal processing for communications
Location:
Utveggio
Presentation Time:
Wed, 10 Sep, 11:20 - 11:40 Italy Time (UTC +2)
Session Co-Chairs:
Paolo Banelli, University of Perugia and Andreas Brendel, Fraunhofer IIS
Presentation
Discussion
Resources
No resources available.
Session SPCN-L1
SPCN-L1.1: MULTI-AGENT ACTOR-CRITIC WITH HARMONIC ANNEALING PRUNING FOR DYNAMIC SPECTRUM ACCESS SYSTEMS
George Stamatelis, National and Kapodistrian University of Athens, Greece; Angelos-Nikolaos Kanatas, National Technical University of Athens, Greece; George Alexandropoulos, National and Kapodistrian University of Athens, Greece
SPCN-L1.2: MACHINE LEARNING-BASED SOURCE-MATCHED CHANNEL CODING FOR SPEECH TRANSMISSION
Oemer Karakas, Andreas Brendel, Marco Breiling, Guillaume Fuchs, Sahana Raghunandan, Fraunhofer IIS, Germany; Wolfgang Gerstacker, FAU Erlangen-Nuernberg, Germany
SPCN-L1.3: On Neural-Network Representation of Wireless Self-Interference for Inband Full-Duplex Systems
Gerald Enzner, Aleksej Chinaev, Carl von Ossietzky University Oldenburg, Germany; Aydin Sezgin, Ruhr-Universität Bochum, Germany
SPCN-L1.4: Optimal Resource Management for Wireless Cooperative Edge Learning with Energy Harvesting
Francesco Binucci, Paolo Banelli, University of Perugia, Italy
SPCN-L1.5: COLLABORATIVE EDGE INFERENCE VIA SEMANTIC GROUPING UNDER WIRELESS CHANNEL CONSTRAINTS
Mateus Mota, Mattia Merluzzi, Emilio Calvanese Strinati, CEA-Leti, France