Weighted autocorrelation-based F0 estimation for distant-talking interaction with a distributed microphone network

A distant-talking scenario is addressed, where a distributed microphone network provides multi-channel input sequences to process for speaker modeling purposes. Possible related applications are speaker tracking and distant-talking speech recognition, given a noisy and reverberant environment with one or more speakers. The paper investigates on the use of a multi-channel version of a weighted autocorrelation (WAUTOC) based F0 estimation method, with the purpose of deriving a common excitation model. Experiments conducted on a real database show the advantages and the robustness of the proposed method in extracting the fundamental frequency with no regard about the microphone and talker position as well as head orientation.