US 9,813,810 B1
Multi-microphone neural network for sound recognition
Rajeev Conrad Nongpiur, Palo Alto, CA (US)
Assigned to GOOGLE INC., Mountain View, CA (US)
Filed by Google Inc., Mountain View, CA (US)
Filed on Jan. 5, 2016, as Appl. No. 14/988,047.
Int. Cl. H04R 3/12 (2006.01); H04R 3/00 (2006.01); H04R 1/40 (2006.01); G10L 25/51 (2013.01); G06N 3/08 (2006.01)
CPC H04R 3/005 (2013.01) [G06N 3/08 (2013.01); G10L 25/51 (2013.01); H04R 1/406 (2013.01); H04R 2201/405 (2013.01); H04R 2430/20 (2013.01)] 23 Claims
OG exemplary drawing
 
1. A method comprising:
generating a plurality of free-field array impulse responses representing impulse responses of a plurality of microphones in free-field conditions over a plurality of directions based on sound events received by the microphones;
generating a first plurality of array impulse responses that model a plurality of simulated environments of different reverberation times, wherein the simulated environments differ from the free-field conditions in which the free-field array impulse responses are generated;
generating a second plurality of array impulse responses in one or more actual environments, wherein the one or more actual environments differ from the free-field conditions in which the free-field array impulse responses are generated; and
training a neural network for sound recognition based on one or more of the free-field array impulse responses, the first plurality of array impulse responses, and the second plurality of array impulse responses, wherein training the neural network for sound recognition includes:
applying positive training labels to input sound signals corresponding to sound events from one or more prescribed directions; and
applying negative training labels are applied to input sound signals corresponding to sound events from directions other than the one or more prescribed directions.