Evaluating Speech Separation Systems

  • Daniel P. W. Ellis


Speech Recognition Automatic Speech Recognition Speech Recognition System Clean Speech Word Error Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Barker, J., Cooke, M., and Ellis, D., 2004, Decoding speech in the presence of other sources, submitted to Speech Communication.Google Scholar
  2. Bell, A.J. and Sejnowski, T.J., 1995, An information-maximization approach to blind separation and blind deconvolution, Neural Computation, 7(6): 1129–1159.Google Scholar
  3. Bourlard, H., Hermansky, H., and Morgan, N., 1996, Towards increasing speech recognition error rates, Speech Communication, pages 205–231.Google Scholar
  4. Brown, G. J. and Cooke, M., 1994, Computational auditory scene analysis, Computer speech and language, 8:297–336.Google Scholar
  5. Bush, V., 1945, As we may think. The Atlantic Monthly.Google Scholar
  6. Cherry, E.G., 1953, Some experiments on the recognition of speech with one and two ears. J. Acoust. Soc. Am., 25:975–979.CrossRefGoogle Scholar
  7. Clarkson, B., Sawhney, N., and Pentland, A., 1998, Auditory context awareness via wearable computing, in Proc. Perceptual User Interfaces Workshop.Google Scholar
  8. Cooke, M.P., 1991, Modelling auditory processing and organisation. Ph.D. thesis, Department of Computer Science, University of Sheffeld.Google Scholar
  9. Cooke, M., Green, P., Josifovski, L., and Vizinho, A., 2001, Robust automatic speech recognition with missing and unreliable acoustic data, Speech Communication, 34(3):267–285.CrossRefGoogle Scholar
  10. Crawford, M.D., Brown, G.J., Cooke, M.P., and Green, P.D., 1994, Design, collection and analysis of amulti-simultaneous-speaker corpus, In Proc. Inst. Acoustics, volume 5, pages 183–190.Google Scholar
  11. Ellis, D.P.W., 1996, Prediction-driven computational auditory scene analysis. Ph.D. thesis, Department of Electrical Engineering and Computer Science, M.I.T.Google Scholar
  12. Hu, G. and Wang, D.L., 2003, Monaural speech separation, in Advances in NIPS 13, Cambridge MA. MIT Press.Google Scholar
  13. Lane, H. and Tranel, B., 1971, The Lombard sign and the role of hearing in speech. J. Speech and Hearing Res., (14):677–709.Google Scholar
  14. Morgan, N., Baron, D., Edwards, J., Ellis, D., Gelbart, D., Janin, A., Pfau, T., Shriberg, E., and Stolcke, A., 2001, The meeting project at ICSI, in Proc. Human Lang. Tech. Conf., pages 246–252.Google Scholar
  15. Pallet, D.S., 1985, Performance assessment of automatic speech recognizers. J. Res. Natl. Bureau of Standards, 90:371–387.Google Scholar
  16. Pearce, D. and Hirsch, H.-G., 2000, The AURORA experimental framework for the performance evaluation of speech recognition systems under noisy conditions, in Proc. ICSLP’ 00, volume 4, pages 29–32, Beijing, China.Google Scholar
  17. Roweis, S., 2001, One-microphone source separation, in Advances in NIPS 11, pages 609–616. MIT Press, Cambridge MA.Google Scholar
  18. Schmidt-Nielsen, A., Marsh, E., Tardelli, J., Gatewood, P., Kreamer, E., Tremain, T., Cieri, C., and Wright, J., 2000, Speech in Noisy Environments (SPINE), Evaluation Audio. Linguistic Data Consortium, Philadelphia PA.Google Scholar
  19. Thiede, T., Treurniet. W.C., Bitto, R., Schmidmer, C. Sporer, T., Beerends, J.G., Colomes, C., Keyhl, M., Stoll, G., Brandeburg, K., and Feiten, B., 2000, PEAQ-the ITU standard for objective measurement of perceived audio quality, J. Audio Eng. Soc., 48(1/2).Google Scholar
  20. Weintraub, M., 1985, A theory and computational model of auditory monoaural sound separation. Ph.D. thesis, Department of Electrical Engineering, Stanford University.Google Scholar
  21. Yu, H., Finke, M., and Waibel, A., 1999, Progress in automatic meeting transcription.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Daniel P. W. Ellis
    • 1
  1. 1.LabROSA, Columbia UniversityNew YorkUSA

Personalised recommendations