Speech recognition for a humanoid with motor noise utilizing missing feature theory

Yoshitaka Nishimura, Mitsuru Ishizuka, Kazuhiro Nakadai, Mikio Nakano, Hiroshi Tsujino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Automatic speech recognition (ASR) is essential for a human-humanoid communication. One of the main problems with ASR is that a humanoid inevitably generates motor noises. These noises are easily captured by the humanoid's microphones because the noise sources are closer to the microphones than the target speech source. Thus, the signal-to-noise ratio (SNR) of input speech becomes quite low (sometimes less than 0 dB). However, it is possible to estimate these noises by using information about the humanoid's own motions and gestures. In this paper we propose a method to improve ASR for a humanoid with motor noises by utilizing the information about the humanoid's motions/gestures. The method consists of psychologically-inspired noise suppression and missing-feature-theory-based ASR (MFT-ASR). The proposed noise suppression technique adds white noise after noise suppression which does not improve SNR, but it is suitable for MFT-ASR. This is inspired by the fact that noise addition sometimes helps human perception as described in Gestalt psychology. MFT-ASR improves ASR by masking unreliable acoustic features in the input sound. The information obtained on motion/gesture is used for estimating reliability of acoustic features in MFT-ASR. We evaluated the proposed method with noisy speech recorded by Honda ASIMO in a room with reverberation. The noise data contained 32 kinds of noises: motor noises without motions, gesture noises, walking noises, and so on. The experimental results show that the proposed method outperforms the conventional multi-condition training technique.

Original languageEnglish
Title of host publicationProceedings of the 2006 6th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS
Pages26-33
Number of pages8
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 6th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS - Genoa
Duration: 2006 Dec 42006 Dec 6

Other

Other2006 6th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS
CityGenoa
Period06/12/406/12/6

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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  • Cite this

    Nishimura, Y., Ishizuka, M., Nakadai, K., Nakano, M., & Tsujino, H. (2006). Speech recognition for a humanoid with motor noise utilizing missing feature theory. In Proceedings of the 2006 6th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS (pp. 26-33). [4115576] https://doi.org/10.1109/ICHR.2006.321359