Parthasarathi, Sree Hari KrishnanBourlard, HervéGatica-Perez, Daniel2011-07-062011-07-062011-07-06201110.21437/Interspeech.2011-390https://infoscience.epfl.ch/handle/20.500.14299/69394We present a comprehensive study of linear prediction residual for speaker diarization on single and multiple distant microphone conditions in privacy-sensitive settings, a requirement to analyze a wide range of spontaneous conversations. Two representations of the residual are compared, namely real-cepstrum and MFCC, with the latter performing better. Experiments on RT06eval show that residual with subband information from 2.5 kHz to 3.5 kHz and spectral slope yields a performance close to traditional MFCC features. As a way to objectively evaluate privacy in terms of linguistic information, we perform phoneme recognition. Residual features yield low phoneme accuracies compared to traditional MFCC features.text::conference output::conference proceedings::conference paper