Robust ego noise suppression of a robot

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6096 LNAI, Issue PART 1, 2010, Pages 62-71

  Ince, Gökhan ^a,c   Nakadai, Kazuhiro ^a,c   Rodemann, Tobias ^b   Tsujino, Hiroshi ^a   Imura, Jun Ichi ^c  

^a HONDA RESEARCH INSTITUTE JAPAN CO LTD   (Japan)

^b HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

^c TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Ego noise; microphone array; missing feature theory; noise reduction; robot audition; speech recognition

Indexed keywords

EGO NOISE; MICROPHONE ARRAY; MISSING FEATURE THEORY; NOISE REDUCTION; ROBOT AUDITION;

ACOUSTIC NOISE; ACOUSTIC NOISE MEASUREMENT; AUDITION; FEATURE EXTRACTION; INDUSTRIAL ENGINEERING; INTELLIGENT SYSTEMS; MICROPHONES; RELIABILITY THEORY; ROBOTS;

SPEECH RECOGNITION;

EID: 78651479949     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-13022-9_7     Document Type: Conference Paper

References (15)

1. Sato, M., Sugiyama, A., Ohnaka, S.: An adaptive noise canceller with low signal-distortion based on variable stepsize subfilters for human-robot communication. IEICE Trans. Fundamentals E88-A(8), 2055-2061 (2004)
2. Nishimura, Y., Nakano, M., Nakadai, K., Tsujino, H., Ishizuka, M.: Speech Recognition for a Robot under its Motor Noises by Selective Application of Missing Feature Theory and MLLR. In: ISCA Tutorial and Research Workshop on Statistical And Perceptual Audition (2006)
3. Ito, A., Kanayama, T., Suzuki, M., Makino, S.: Internal Noise Suppression for Speech Recognition by Small Robots. In: Interspeech, pp. 2685-2688 (2005)
4. Ince, G., Nakadai, K., Rodemann, T., Hasegawa, Y., Tsujino, H., Imura, J.: Ego Noise Suppression of a Robot Using Template Subtraction. In: Proc. of the IEEE/RSJ International Conference on Robots and Intelligent Systems (IROS), pp. 199-204 (2009)
5. Cohen, I.: Noise Estimation by Minima Controlled Recursive Averaging for Robust Speech Enhancement. IEEE Signal Processing Letters 9(1) (2002)
6. Boll, S.: Suppression of Acoustic Noise in Speech Using Spectral Subtraction. IEEE Transactions on Acoustics, Speech, and Signal Processing ASSP-27(2) (1979)
7. Raj, B., Stern, R.M.: Missing-feature approaches in speech recognition. IEEE Signal Processing Magazine 22, 101-116 (2005)
8. Yamamoto, S., Nakadai, K., Nakano, M., Tsujino, H., Valin, J.M., Komatani, K., Ogata, T., Okuno, H.G.: Real-time robot audition system that recognizes simultaneous speech in the real world. In: Proc. of the IEEE/RSJ International Conference on Robots and Intelligent Systems, IROS (2006)
9. Takahashi, T., Yamamoto, S., Nakadai, K., Komatani, K., Ogata, T., Okuno, H.G.: Soft Missing-Feature Mask Generation for Simultaneous Speech Recognition System in Robots. In: Proceedings of International Conference on Spoken Language Processing (Interspeech), pp. 992-997 (2008)
10. Parra, L.C., Alvino, C.V.: Geometric Source Separation: Merging Convolutive Source Separation with Geometric Beamforming. IEEE Trans. Speech Audio Process 10(6), 352-362 (2002)
11. Ince, G., Nakadai, K., Rodemann, T., Hasegawa, Y., Tsujino, H., Imura, J.: A Hybrid Framework for Ego Noise Cancellation of a Robot. In: Proc. of the IEEE/RSJ International Conference on Robotics and Automation, ICRA (to appear, 2010)
12. Schmidt, R.: Multiple emitter location and signal parameter estimation. IEEE Trans. on Antennas and Propagation 34(3), 276-280 (1986)
13. Valin, J.-M., Rouat, J., Michaud, F.: Enhanced Robot Audition Based on Microphone Array Source Separation with Post-Filter. In: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2123-2128 (2004)
14. Nakajima, H., Nakadai, K., Hasegawa, Y., Tsujino, H.: Adaptive step-size parameter control for real-world blind source separation. In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 149-152 (2008)
15. Nishimura, Y., Shinozaki, T., Iwano, K., Furui, S.: Noise-robust speech recognition using multi-band spectral features. In: Proc. of 148th Acoustical Society of America Meetings, vol. 1aSC7 (2004)