Cognitive Models for Acoustic and Audiovisual Sound Source Localization (2020)
Abstract / truncated to 115 words
Sound source localization algorithms have a long research history in the field of digital signal processing. Many common applications like intelligent personal assistants, teleconferencing systems and methods for technical diagnosis in acoustics require an accurate localization of sound sources in the environment. However, dynamic environments entail a particular challenge for these systems. For instance, voice controlled smart home applications, where the speaker, as well as potential noise sources, are moving within the room, are a typical example of dynamic environments. Classical sound source localization systems only have limited capabilities to deal with dynamic acoustic scenarios. In this thesis, three novel approaches to sound source localization that extend existing classical methods will be presented. The first ... toggle 7 keywordssound source localization – audiovisual signal processing – kalman filter – robot audition – binaural models – causal models – microphone array processing
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