US 11,922,965 B2
Direction of arrival estimation apparatus, model learning apparatus, direction of arrival estimation method, model learning method, and program
Masahiro Yasuda, Tokyo (JP); and Yuma Koizumi, Tokyo (JP)
Assigned to NIPPON TELEGRAPH AND TELEPHONE CORPORATION, Tokyo (JP)
Appl. No. 17/639,675
Filed by NIPPON TELEGRAPH AND TELEPHONE CORPORATION, Tokyo (JP)
PCT Filed Feb. 4, 2020, PCT No. PCT/JP2020/004011
§ 371(c)(1), (2) Date Mar. 2, 2022,
PCT Pub. No. WO2021/044647, PCT Pub. Date Mar. 11, 2021.
Claims priority of application No. PCT/JP2019/034829 (WO), filed on Sep. 4, 2019.
Prior Publication US 2022/0301575 A1, Sep. 22, 2022
Int. Cl. G10L 21/0232 (2013.01); G10L 21/0208 (2013.01); G10L 21/0216 (2013.01); G10L 25/18 (2013.01); G10L 25/30 (2013.01); H04R 1/40 (2006.01); H04R 3/00 (2006.01)
CPC G10L 21/0232 (2013.01) [G10L 25/18 (2013.01); G10L 25/30 (2013.01); H04R 1/406 (2013.01); H04R 3/005 (2013.01); G10L 2021/02082 (2013.01); G10L 2021/02166 (2013.01); H04R 2201/401 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A direction-of-arrival estimation device comprising a processor configured to execute a method comprising:
receiving input of a real spectrogram extracted from a complex spectrogram of acoustic data and an acoustic intensity vector extracted from the complex spectrogram;
generating an estimated reverberation portion of the acoustic intensity vector;
receiving input of the real spectrogram and the acoustic intensity vector from which the reverberation portion has been subtracted;
generating a time frequency mask for noise suppression; and
determining a sound source direction-of-arrival based on an acoustic intensity vector formed by applying the time frequency mask to the acoustic intensity vector from which the reverberation portion has been subtracted.