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@ARTICLE{Schoepe:1022166,
      author       = {Schoepe, Thorben and Gutierrez-Galan, Daniel and
                      Dominguez-Morales, Juan P and Greatorex, Hugh and
                      Jimenez-Fernandez, Angel and Linares-Barranco, Alejandro and
                      Chicca, Elisabetta},
      title        = {{C}losed-loop sound source localization in neuromorphic
                      systems},
      journal      = {Neuromorphic computing and engineering},
      volume       = {3},
      number       = {2},
      issn         = {2634-4386},
      address      = {Bristol},
      publisher    = {IOP Publishing Ltd.},
      reportid     = {FZJ-2024-01287},
      pages        = {024009 -},
      year         = {2023},
      abstract     = {Sound source localization (SSL) is used in various
                      applications such as industrial noise-control,speech
                      detection in mobile phones, speech enhancement in hearing
                      aids and many more. Newestvideo conferencing setups use SSL.
                      The position of a speaker is detected from the difference in
                      theaudio waves received by a microphone array. After
                      detection the camera focuses onto the locationof the
                      speaker. The human brain is also able to detect the location
                      of a speaker from auditorysignals. It uses, among other
                      cues, the difference in amplitude and arrival time of the
                      sound wave atthe two ears, called interaural level and time
                      difference. However, the substrate and
                      computationalprimitives of our brain are different from
                      classical digital computing. Due to its low powerconsumption
                      of around 20 W and its performance in real time the human
                      brain has become agreat source of inspiration for emerging
                      technologies. One of these technologies is
                      neuromorphichardware which implements the fundamental
                      principles of brain computing identified until todayusing
                      complementary metal-oxide-semiconductor technologies and new
                      devices. In this work wepropose the first neuromorphic
                      closed-loop robotic system that uses the interaural time
                      differencefor SSL in real time. Our system can successfully
                      locate sound sources such as human speech. In aclosed-loop
                      experiment, the robotic platform turned immediately into the
                      direction of the soundsource with a turning velocity
                      linearly proportional to the angle difference between sound
                      sourceand binaural microphones. After this initial turn, the
                      robotic platform remains at the direction ofthe sound
                      source. Even though the system only uses very few resources
                      of the available hardware,consumes around 1 W, and was only
                      tuned by hand, meaning it does not contain any learning
                      atall, it already reaches performances comparable to other
                      neuromorphic approaches. The SSLsystem presented in this
                      article brings us one step closer towards neuromorphic
                      event-basedsystems for robotics and embodied computing.},
      cin          = {PGI-15},
      ddc          = {621.3},
      cid          = {I:(DE-Juel1)PGI-15-20210701},
      pnm          = {5234 - Emerging NC Architectures (POF4-523)},
      pid          = {G:(DE-HGF)POF4-5234},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001064496000001},
      doi          = {10.1088/2634-4386/acdaba},
      url          = {https://juser.fz-juelich.de/record/1022166},
}