  To phased microphone array for sound source localization, algorithm with both
high computational efficiency and high precision is a persistent pursuit. In
this paper convolutional neural network (CNN) a kind of deep learning is
preliminarily applied as a new algorithm. At high frequency CNN can reconstruct
the sound localizations with excellent spatial resolution as good as DAMAS,
within a very short time as short as conventional beamforming. This exciting
result means that CNN perfectly finds source distribution directly from
cross-spectral matrix without given propagation function in advance, and thus
CNN deserves to be further explored as a new algorithm.
