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Title of the item:

Robot Audition and Computational Auditory Scene Analysis

Title :
Robot Audition and Computational Auditory Scene Analysis
Authors :
Kazuhiro Nakadai
Hiroshi G. Okuno
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Subject Terms :
automatic speech recognition
multimodal integration
open-source softwares
robot audition
sound-source localization
sound source separation
Computer engineering. Computer hardware
TK7885-7895
Control engineering systems. Automatic machinery (General)
TJ212-225
Source :
Advanced Intelligent Systems, Vol 2, Iss 9, Pp n/a-n/a (2020)
Publisher :
Wiley, 2020.
Publication Year :
2020
Collection :
LCC:Computer engineering. Computer hardware
Document Type :
article
File Description :
electronic resource
Language :
English
ISSN :
2640-4567
20200005
Relation :
https://doaj.org/toc/2640-4567
DOI :
10.1002/aisy.202000050
Access URL :
https://doaj.org/article/2cfd6d3613b24eb4baf627f17f4cbe5a
Accession Number :
edsdoj.2cfd6d3613b24eb4baf627f17f4cbe5a
Academic Journal
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.

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