公开(公告)号：US12080319B2

公开(公告)日：2024-09-03

申请号：US18035934

申请日：2022-06-27

Applicant: Jiangsu University

Inventor： Qirong Mao ,  Lijian Gao ,  Yaxin Shen ,  Qinghua Ren ,  Yongzhao Zhan ,  Keyang Cheng

IPC: G10L25/78 ,  G10L25/18 ,  G10L25/30

CPC classification number: G10L25/78 ,  G10L25/18 ,  G10L25/30

Abstract: The present disclosure provides a weakly-supervised sound event detection method and system based on adaptive hierarchical pooling. The system includes an acoustic model and an adaptive hierarchical pooling algorithm module (AHPA-model), where the acoustic model inputs a pre-processed and feature-extracted audio signal, and predicts a frame-level prediction probability aggregated by the AHPA-module to obtain a sentence-level prediction probability. The acoustic model and a relaxation parameter are jointly optimized to obtain an optimal model weight and an optimal relaxation parameter based for formulating each category of sound event. A pre-processed and feature-extracted unknown audio signal is input to obtain frame-level prediction probabilities of all target sound events (TSEs), and sentence-level prediction probabilities of all categories of TSEs are obtained based on an optimal pooling strategy of each category of TSE. The disclosure has good versatility in being applicable to audio classification, complex acoustic scene, and locating in weakly-supervised sound event detection.