Noise-Robust Double-Talk Detection Based on Normalized Cross Correlation and a Noise Offset
Akihiko K. Sugiyama, Jérôme Berclaz, Miki Sato · 2006
This paper presents a noise-robust double-talk detection algorithm based on normalized cross-correlation and a noise offset. The noise offset alleviates undesirable influence by the background noise existing in the microphone signal. It is estimated from the echo-cancelled signal when its autocorrelation is low and its power is smaller than the echo-replica power. A detection threshold of the new normalized cross-correlation is adaptively controlled based on the echo-to-NES (near-end speech) ratio. Simulation results demonstrate superior performance of the new algorithm.