A robust audio identification for enhancing audio-based indoor localization

Nowadays, user localization in indoor environments is more necessary to build many location-based services. This paper presents a robust audio identification method for enhancing a real-time indoor localization system on a mobile device using the audio signals emitted by nearby loudspeakers. The proposed audio identification method deals with various noise distortions due to different noisy indoor locations by using foreground/background audio separation, prominent spectral pitch-based binary audio fingerprinting, and spectral peak-triplet-based audio fingerprinting. Experimental results confirm that the proposed audio identification method is quite robust in different noise conditions and achieves preliminary promising results for discriminating the location and orientation of a user in large indoor locations.

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