Soft missing-feature mask generation for Robot Audition

Soft missing-feature mask generation for Robot Audition

This paper describes an improvement in automatic speech recognition (ASR) for robot audition by introducing Missing Feature Theory (MFT) based on soft missing feature masks (MFM) to realize natural human-robot interaction. In an everyday environment, a robot’s microphones capture various sounds besi...

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Bibliographic Details
Main Authors: Takahashi Toru, Nakadai Kazuhiro, Komatani Kazunori, Ogata Tetsuya, Okuno Hiroshi G.
Format: Article
Language:English
Published: De Gruyter 2010-03-01
Series:Paladyn: Journal of Behavioral Robotics
Subjects:
robot audition
hark
missing-feature-theory
soft mask generation
simultaneous speech recognition
automatic speech recognition
sound source separation
sound localization
Online Access:https://doi.org/10.2478/s13230-010-0005-1

Internet

https://doi.org/10.2478/s13230-010-0005-1

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