机器人自身噪声环境下的自动语音识别
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摘要
当机器人移动身体任何部位时,都会不可避免地产生自身噪声。这些自身噪声由身体关节或其他硬件设备如风扇等引起。由于自身噪声距离机器人麦克风较近,较目标声源更容易被获取。该文根据机器人自身噪声种类,提出了一种将谱减法、关节噪声模板减法、基于标注区域的倒谱均值减法以及多条件训练相结合的方法,从而估计和抑制自身噪声。一系列实验证明了所提出的方法可以有效地减少自身噪声影响,提高语音识别的鲁棒性。
Robots inevitably produce noise when they are moving any part of their body.Such noise is caused by the various body joint motors as well as the CPU cooling fans.Moreover,these noises are easily captured by the robots'microphones because they are closer to the microphones than the target speech source.This paper presents a de-noising method using the spectral subtraction,joint noise template substraction,labeled area cepstral mean substraction and multi-condition training to estimate and suppress robot noise.Tests show that this method significantly reduces the effect of robot noise which enhances the automatic speech recognition.
Robots inevitably produce noise when they are moving any part of their body.Such noise is caused by the various body joint motors as well as the CPU cooling fans.Moreover,these noises are easily captured by the robots'microphones because they are closer to the microphones than the target speech source.This paper presents a de-noising method using the spectral subtraction,joint noise template substraction,labeled area cepstral mean substraction and multi-condition training to estimate and suppress robot noise.Tests show that this method significantly reduces the effect of robot noise which enhances the automatic speech recognition.
引文
[1]Ince G,Nakadai K,Rodemann T,et al.A hybrid framework for ego noise cancellation of a robot[C]//2010 IEEE International Conference on Robotics and Automation(ICRA).Piscataway,NJ:IEEE Press,2010:3623-3628.
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[4]Nakadai K,Lourens T,Okuno H G,et al.Active audition for humanoid[C]//Proc of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence.Palo Alto,CA:AAAI Press,2000:832-839.
[5]Even J,Sawada H,Saruwatari H,et al.Semi-blind suppression of internal noise for hands-free robot spoken dialog system[C]//Proc 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Piscataway,NJ:IEEE Press,2009:658-663.
[6]Cohen I,Berdugo B.Speech enhancement for non-stationary noise environments[J].Signal Processing,2001,81(1):2403-2418.
[7]Cohen I,Berdugo B.Noise estimation by minima controlled recursive averaging for robust speech enhancement[J].IEEE Signal Processing Letters,2002,9(1):12-15.
[8]Ito A,Kanayama T,Suzuki M,et al.Internal noise suppression for speech recognition by small robots[J].IEICE Technical Report Speech,2005,105:43-48.
[9]Nishimura Y,Ishizuka M,Nakadai K,et al.Speech recognition for a humanoid with motor noise utilizing missing feature theory[C]//2006 6th IEEE-RAS International Conference on Humanoid Robots.Piscataway,NJ:IEEE Press,2006:26-33.
[10]Ince G,Nakadai K,Rodemann T,et al.Incremental learning for ego noise estimation of a robot[C]//2011IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Piscataway,NJ:IEEE Press,2011:131-136.
[11]Ince G,Nakadai K,Rodemann T,et al.Ego noise suppression of a robot using template subtraction[C]//Proceedings of the 2009IEEE/RSJ International Conference on Intelligent Robots and Systems.Piscataway,NJ:IEEE Press,2009:199-204.
[12]Boll S.Suppression of acoustic noise in speech using spectral subtraction[J].Processing IEEE Transactions on Acoustics Speech&Signal,1979,27(2):113-120.
[13]Viikki O,Bye D,Laurila K.A recursive feature vector normalization approach for robust speech recognition in noise[C]//Proc 1998 IEEE International Conference on Acoustics,Speech and Signal Processing.Piscataway,NJ:IEEE Press,1998,2:733-736.
[2]Breazeal C L.Designing Sociable Robots[M].Boston,MA:MIT Press,2004.
[3]Miwa H,Okuchi T,Itoh K,et al.A new mental model for humanoid robots for human friendly communication introduction of learning system,mood vector and second order equations of emotion[C]//Proc 2003 IEEE International Conference on Robotics and Automation(ICRA).Piscataway,NJ:IEEE Press,2003,3:3588-3593.
[4]Nakadai K,Lourens T,Okuno H G,et al.Active audition for humanoid[C]//Proc of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence.Palo Alto,CA:AAAI Press,2000:832-839.
[5]Even J,Sawada H,Saruwatari H,et al.Semi-blind suppression of internal noise for hands-free robot spoken dialog system[C]//Proc 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Piscataway,NJ:IEEE Press,2009:658-663.
[6]Cohen I,Berdugo B.Speech enhancement for non-stationary noise environments[J].Signal Processing,2001,81(1):2403-2418.
[7]Cohen I,Berdugo B.Noise estimation by minima controlled recursive averaging for robust speech enhancement[J].IEEE Signal Processing Letters,2002,9(1):12-15.
[8]Ito A,Kanayama T,Suzuki M,et al.Internal noise suppression for speech recognition by small robots[J].IEICE Technical Report Speech,2005,105:43-48.
[9]Nishimura Y,Ishizuka M,Nakadai K,et al.Speech recognition for a humanoid with motor noise utilizing missing feature theory[C]//2006 6th IEEE-RAS International Conference on Humanoid Robots.Piscataway,NJ:IEEE Press,2006:26-33.
[10]Ince G,Nakadai K,Rodemann T,et al.Incremental learning for ego noise estimation of a robot[C]//2011IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Piscataway,NJ:IEEE Press,2011:131-136.
[11]Ince G,Nakadai K,Rodemann T,et al.Ego noise suppression of a robot using template subtraction[C]//Proceedings of the 2009IEEE/RSJ International Conference on Intelligent Robots and Systems.Piscataway,NJ:IEEE Press,2009:199-204.
[12]Boll S.Suppression of acoustic noise in speech using spectral subtraction[J].Processing IEEE Transactions on Acoustics Speech&Signal,1979,27(2):113-120.
[13]Viikki O,Bye D,Laurila K.A recursive feature vector normalization approach for robust speech recognition in noise[C]//Proc 1998 IEEE International Conference on Acoustics,Speech and Signal Processing.Piscataway,NJ:IEEE Press,1998,2:733-736.