Signal separation method, signal separation device and...

Data processing: measuring – calibrating – or testing – Measurement system – Measured signal processing

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C702S189000, C702S195000, C702S196000, C375S232000, C375S377000, C704S203000, C704S205000

Reexamination Certificate

active

07496482

ABSTRACT:
A method and a device for signal separation. First, values of signals observed by M sensors are transformed into frequency domain values, and these frequency domain values are used to calculate relative values of the observed values between the sensors at each frequency. These relative values are clustered into N clusters, and the representative value of each cluster is calculated. Then, using these representative values, a mask is produced to extract the values of the signals emitted by V (1≦V≦M) signal sources from the frequency-domain signal values, and this mask is applied to the frequency-domain signal values. After that, if V=1 then the limited signal is output directly as a separated signal, while if V≧2 then the separated values are obtained by separating this limited signal with separation techniques such as ICA.

REFERENCES:
patent: 5786872 (1998-07-01), Miyazaki et al.
patent: 6011824 (2000-01-01), Oikawa et al.
patent: 2003/0103561 (2003-06-01), Rickard et al.
patent: 2004-145172 (2004-05-01), None
Scott Rickard et al., “On the Approximate W-Disjoint Orthogonality of Speech”, Proc. ICASSP, vol. 1, pp. 529 to 532, 2002.
Hiroshi Saruwatari, “[Invited Paper] Blind Source Separation for Speech and Acoustic Signals” The Institute of Electronics, Information and Communication Engineers, vol. 101, No. 669, CS2001-134, pp. 59 to 66, Feb. 25, 2002.
Shoko Araki et al., “Jikan Shuhasu Masking to ICA no Heiyo ni yoru Ongensu > Microphone-su no Baai no Blind Ongen Bunri”, The Acoustical Society of Japan (ASJ)2003 Nen Shuki Kenkyu Happyokai Koen Ronbunshu -I-, 1-P-5, pp. 587 to 588, Sep. 17, 2003.
Aapo Hyvaerinen, Juha Karhunen, Erkki OJA, “Independent Component Analysis” John Wiley & Sons, ISBN 0-471-40540, 2001.
H. Sawada, R. Mukai, S. Araki and S. Makino, “A Robust and Precise Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation,” Proc. the 4thInternational Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), pp. 505-510, 2003.
S. Rickard, R. Balan, J. Rosca, “Real-Time Time-Frequency Based Blind Source Separation” 3rdInternational Conference on Independent Component Analysis and Blind Source Separation (ICA2001), San Diego, p. 651-656, Dec. 2001.
F. Abrard, Y. Deville, P. White, “From Blind Source Separtion To Blind Source Cancellation in the Underdetermined Case: A New Approach Based on Time-Frequency Anaysis” Proceedings of th e3rd International Conference on Independent Component Analysis and Signal Separation (ICA'2001), pp. 734-739, San Diego, California, Dec. 2001.
Y. Deville, “Temporal and time-frequency correlation-based blind source separation methods,” in Proc., ICASSP2003, pp. 1059-1064, Apr. 2003.
Morio Onoe (trans.): “Pattern Classification,” Shingijutsu Communications, ISBN 4-915851-24-9, Chapter 10.
Shoko Araki: “Blind Separation of More Speech Signals than Sensors using Time-Frequency Masking and Mixing Estimation” 1-P-4, Sep. 2003.
Audrey Blin et al.: Blind Source Separation when Speech Signals Outnumber Sensors using a Sparseness—Mixing Matrix Estimation (SMME), International Workshop on Acoustic Echo and Noise Control (IWAENC2003), Sep. 2003.
Shoko Araki et al.: “Underdetermined Blind Separation of Convolutive Mixtures of Speech by Combining Time-frequency Masks and ICA” Mo4.D.1 pp. I-321 to I-324, 2004.
Audrey Blin et al.: Undertermined Blind Source Separation for Convolutive Mixtures Exploiting a Sparseness—Mixing Matrix Estimation (SMME), Th.P1.11, IV-3139-3142, 2004.
Shoko Araki et al.: “Underdetermined Blind Separation for Speech in Real Environments with Sparseness and ICA” 0-7803- 8484-9/04/$20.00 © 2004 IEEE, III-881-884.
Audrey Blin et al.: “A Sparseness- Mixing Matrix Estimation (SMME) Solving the Underdetermined BSS for Convolutive Mixtures” 0-7803-9595-9/04/$20.00 © 2004 IEEE IV-85-88.
Shoko Araki et al.: “Underdetermined Blind Speech Separation with Directivity Pattern based Continuous Mask and ICA” EUSIPCO (European Signal Processing Conference), pp. 1991-1994, Sep. 6-10, 2004.
Shoko Araki et al.: “Underdetermined Blind Separation of Convolutive Mixtures of Speech with Directivity Pattern Based Mask and ICA” C.G. Puntonet and A. Prieto (Eds.) ICA 2004, LNCS 3195, pp. 898-905, 2004.
Shoko Araki et al.: Source Extraction from Speech Mixtures with Null-Directivity Pattern based Mask HSCMA, Rutgers University, Piscataway, New Jersey, USA, pp. d-1-2, Mar. 17-18, 2005.
Stefan Winter et al.: “Overcomplete BSS for Convolutive Mixtures Based on Hierarchical Clustering” C.G. Puntonet and A. Prieto (Eds.): ICA 2004, LNCS 3195, pp. 652-660, 2004.
Stefan Winter et al.: “Hierarchical clustering to overcomplete BSS for convolution mixtures” Workshop on Statistcal and Perceptual Audio Processing SAPA-2004, Oct. 3, 2004, Jeju, Korea.
A. Ossadtchi et al.: “Over-complete Blind source separation by applying sparse decomposition and information theoretic based probabilistic approach” ©2000 HRL Laboratories, LLC, all rights reserved.
J. Michael Peterson et al.: “A Probabilistic Approach for Blind Source Separation of Underdetermined Convolutive Mixtures” 0-7803-7663-3/03/$17.00 © 2003 IEEE, VI-581-584.
Stefan Winter et al.: “Hierarchical clustering applied to overcomplete BSS for convolutive mixtures” NTT Communication Science Laboratories, NTT Corporation.
Shoko Araki et al., “Jikan Shuhasu Masking to ICA no Heiyo ni yoru Ongensu > Microphone-su no Baai no Blind Ongen Bunri”, The Acoustical Society of Japan (ASL)2003 Nen Shuki Kenkyu Happyokai Koen Ronbunshu -I-, 1-P-5, pp. 587 to 588, Sep. 17, 2003. (submitting English Translation of Introduction only, reference Previously filed on Jun. 17, 2005).
Futoshi Asano, et al. “Combined Approach of Array Processing and Independent Component Analysis for Blind Separation of Acoustic Signals”, IEEE Transactions on Speech and Audio Processing, vol. 11, No. 3, May 2003, XP-011079702, pp. 204-215.
Pau Bofill, et al. “Blind Separation of more Sources Than Mixtures Using Sparsity of Their Short-time Fourier Transform”, International Workshop on Independent Component Analysis and Blind Signal Separation, Jun. 19, 2000, XP-008005807, pp. 87-92.
Shoko Araki, et al. “Blind Separation of More Speech than Sensors with Less Distortion by Combining Sparseness and ICA” International Workshop on Acoustic Echo and Noise Control, Sep. 2003, XP-002459797, pp. 271-274.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Signal separation method, signal separation device and... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Signal separation method, signal separation device and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Signal separation method, signal separation device and... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4072330

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.