Invention Grant
- Patent Title: Sim-to-real learning of 2D multiple sound source localization
-
Application No.: US16804806Application Date: 2020-02-28
-
Publication No.: US11676032B2Publication Date: 2023-06-13
- Inventor: Guillaume Jean Victor Marie Le Moing , Don Joven Ravoy Agravante , Phongtharin Vinayavekhin , Jayakorn Vongkulbhisal , Tadanobu Inoue , Asim Munawar
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Randy Emilio Tejeda
- Main IPC: G06N3/084
- IPC: G06N3/084 ; G10L25/51 ; H04R3/00 ; H04R1/40 ; G06N3/044

Abstract:
A computer-implemented method is provided for training a multi-source sound localization model using labeled simulation data and unlabeled real data. The method includes inputting the labeled simulation data and the unlabeled real data respectively into a multi-source sound localization model of a neural network to obtain a localization heatmap from an output layer of the multi-source sound localization model for each of the labeled simulation data and the unlabeled real data. The method further includes inputting the localization heatmap for each of the labeled simulation data and the unlabeled real data into an output discriminator. The method also includes training the output discriminator so that the output discriminator assigns a domain class label to distinguish simulation data from real data. The method additionally includes training, by a hardware process, the multi-source sound localization model by a first adversarial loss for the output discriminator with an original localization model loss.
Public/Granted literature
- US20210271978A1 SIM-TO-REAL LEARNING OF 2D MULTIPLE SOUND SOURCE LOCALIZATION Public/Granted day:2021-09-02
Information query