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A natural integration of virtual sound sources with the real environment soundscape using a natural augmented reality (NAR) headset is discussed in this paper. These NAR headsets consist of dual sensing microphones at each earcup and employ adaptive filtering technique to achieve natural listening in augmented reality applications. We propose an adaptive equalization of the open-back NAR headsets using non-stationary virtual signals to compensate for individualized headphones transfer function (HPTF) and acoustic coupling to seamlessly mix virtual sound with the environmental sound. Training of the NAR headsets are carried out using fast-converging normalized filtered-x least mean square algorithms to respond to changing sound variation. Significant changes in HPTF can be detected online and fast HPTF estimation using normalized least mean square algorithm is employed to update the secondary path estimates.
Author (s): Ranjan, Rishabh; Gan, Woon-Seng
Affiliation:
Nanyang Technological University, Singapore
(See document for exact affiliation information.)
Publication Date:
2016-08-06
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Session subject:
Headphone Personalization / Headphone Transducers: Technology, Measurement, Microdrivers, Smart Control, Simulation
Permalink: https://aes2.org/publications/elibrary-page/?id=18344
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Ranjan, Rishabh; Gan, Woon-Seng; 2016; Adaptive Equalization of Natural Augmented Reality Headset Using Non-Stationary Virtual Signals [PDF]; Nanyang Technological University, Singapore; Paper 2-5; Available from: https://aes2.org/publications/elibrary-page/?id=18344
Ranjan, Rishabh; Gan, Woon-Seng; Adaptive Equalization of Natural Augmented Reality Headset Using Non-Stationary Virtual Signals [PDF]; Nanyang Technological University, Singapore; Paper 2-5; 2016 Available: https://aes2.org/publications/elibrary-page/?id=18344