Learning How to Listen: A Temporal-Frequential Attention Model for Sound Event Detection

In this paper, we propose a temporal-frequential attention model for sound event detection (SED). Our network learns how to listen with two attention models: a temporal attention model and a frequential attention model. Proposed system learns when to listen using the temporal attention model while i...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Yu-Han, Shen, Ke-Xin, He, Wei-Qiang, Zhang
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 29.10.2018
Subjects
Sound
Online AccessGet full text

Cover

More Information
Summary:In this paper, we propose a temporal-frequential attention model for sound event detection (SED). Our network learns how to listen with two attention models: a temporal attention model and a frequential attention model. Proposed system learns when to listen using the temporal attention model while it learns where to listen on the frequency axis using the frequential attention model. With these two models, we attempt to make our system pay more attention to important frames or segments and important frequency components for sound event detection. Our proposed method is demonstrated on the task 2 of Detection and Classification of Acoustic Scenes and Events (DCASE) 2017 Challenge and achieves competitive performance.
ISSN:2331-8422