  Personalized speech enhancement has been a field of active research for
suppression of speechlike interferers such as competing speakers or TV
dialogues. Compared with single channel approaches, multichannel PSE systems
can be more effective in adverse acoustic conditions by leveraging the spatial
information in microphone signals. However, the implementation of multichannel
PSEs to accommodate a wide range of array topology in household applications
can be challenging. To develop an array configuration agnostic PSE system, we
define a spatial feature termed the long short term spatial coherence as the
input feature to a convolutional recurrent network to monitor the voice
activity of the target speaker. As another refinement, an equivalent
rectangular bandwidth scaled LSTSC feature can be used to reduce the
computational cost. Experiments were conducted to compare the proposed PSE
systems, including the complete and the simplified versions with two baselines
using unseen room responses and array configurations in the presence of TV
noise and competing speakers. The results demonstrated that the proposed
multichannel PSE network trained with the LSTSC feature achieved superior
enhancement performance without precise knowledge of the array configurations
and room responses.
