Open AccessRobot Audition and Computational Auditory Scene Analysis
Author(s) -
Nakadai Kazuhiro,
Okuno Hiroshi G.
Publication year - 2020
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202000050
Subject(s) - computer science , robot , preprocessor , robustness (evolution) , noise (video) , speech recognition , active listening , artificial intelligence , software , human–computer interaction , computational auditory scene analysis , psychology , communication , biochemistry , chemistry , image (mathematics) , gene , programming language
Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open‐source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real‐world auditory environments.