A double-talk detection algorithm using a psychoacoustic auditory model

Successful adaptive echo cancellation in telecommunications depends on a control device called a double-talk (DT) detector. DT refers to the situation when signals from both ends of an echo cancellation system are simultaneously active. In the presence of a DT condition, the role of a DT detector is to prevent divergence of the adaptive filter in an echo cancellation system. This paper presents a novel double-talk detection (DTD) algorithm using a psychoacoustic auditory model. The model exploits the frequency masking properties of the human auditory system. It performs an analysis of the far-end signal and removes spectral components below a perceptual threshold, to create spectral holes without affecting the perceptual quality of the signal. A DT condition can be detected by monitoring the energy level in the created holes. Simulations with real speech data and comparisons with other DTD algorithms are presented to show the performance of the proposed algorithm.