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2016
Conference Paper
Titel
Open-set microphone classification via blind channel analysis
Abstract
In this paper, we present a new algorithm for open-set microphone classification, which is based on a pre-existing blind channel estimation approach. The proposed method achieves a Rand index above 93% for AAC, MP3 and PCM-encoded recordings from eight different mobile devices.