Robot Audition: Missing Feature Theory Approach and Active Audition

2011 ◽  
pp. 227-244 ◽  
Author(s):  
Hiroshi G. Okuno ◽  
Kazuhiro Nakadai ◽  
Hyun-Don Kim
Keyword(s):  
Theory Approach ◽  
Robot Audition ◽  
Missing Feature Theory ◽  
Missing Feature ◽  
Feature Theory

scholarly journals Soft missing-feature mask generation for Robot Audition

2010 ◽  
Vol 1 (1) ◽  
Author(s):  
Toru Takahashi ◽  
Kazuhiro Nakadai ◽  
Kazunori Komatani ◽  
Tetsuya Ogata ◽  
Hiroshi G. Okuno
Keyword(s):  
Human Robot Interaction ◽  
Sigmoid Function ◽  
Robot Interaction ◽  
Time Frequency ◽  
Sound Source Separation ◽  
Robot Audition ◽  
Frequency Components ◽  
Interaction Task ◽  
Missing Feature Theory ◽  
Missing Feature

AbstractThis 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 besides the user’s utterances. Although sound-source separation is an effective way to enhance the user’s utterances, it inevitably produces errors due to reflection and reverberation. MFT is able to cope with these errors. First, MFMs are generated based on the reliability of time-frequency components. Then ASR weighs the time-frequency components according to the MFMs. We propose a new method to automatically generate soft MFMs, consisting of continuous values from 0 to 1 based on a sigmoid function. The proposed MFM generation was implemented for HRP-2 using HARK, our open-sourced robot audition software. Preliminary results show that the soft MFM outperformed a hard (binary) MFM in recognizing three simultaneous utterances. In a human-robot interaction task, the interval limitations between two adjacent loudspeakers were reduced from 60 degrees to 30 degrees by using soft MFMs.

Hard-mask missing feature theory for robust speaker recognition

2011 ◽  
Vol 57 (3) ◽  
pp. 1245-1250 ◽  
Author(s):  
Shin-cheol Lim ◽  
Sei-jin Jang ◽  
Soek-pil Lee ◽  
Moo Kim
Keyword(s):  
Speaker Recognition ◽  
Hard Mask ◽  
Robust Speaker Recognition ◽  
Missing Feature Theory ◽  
Missing Feature ◽  
Feature Theory
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