[Illinois] Neuroengineering IGERT Symposium: Three Projects to Understand the Cocktail Party Effect

By Malcolm Slaney

Conversational Systems Research Center, Microsoft, Mountain View, CA

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Abstract


Bio

Malcolm Slaney - Microsoft

Malcolm Slaney (Fellow, IEEE) is a Principal Scientist in Microsoft Research's Conversational Systems Research Center in Mountain View, CA. Before that he held the same title at Yahoo! Research, where he worked on multimedia analysis and music- and image-retrieval algorithms in databases with billions of items. He is also a (consulting) Professor at Stanford University's Center for Computer Research in Music and Acoustics (CCRMA), Stanford, CA, where he has led the Hearing Seminar for the last 20 years. Dr. Slaney is also an affiliate professor in the department of Electrical Engineering at the University of Washington. Before Yahoo!, he has worked at Bell Laboratory, Schlumberger Palo Alto Research, Apple Computer, Interval Research, and IBM's Almaden Research Center. For the last several years he has helped lead the auditory and attention groups at the NSF-sponsored Telluride Neuromorphic Cognition Workshop. He is a coauthor, with A. C. Kak, of the IEEE book Principles of Computerized Tomographic Imaging. This book was republished by SIAM in their Classics in Applied Mathematics series. He is coeditor, with S. Greenberg, of the book Computational Models of Auditory Function. Prof. Slaney has served as an Associate Editor of the IEEE TRANSACTIONS ON AUDIO, SPEECH, AND SIGNAL PROCESSING, IEEE MULTIMEDIA MAGAZINE, the PROCEEDINGS OF THE IEEE, and the ACM Transactions on Multimedia Computing, Communications, and Applications.

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Cite this work

Researchers should cite this work as follows:

  • Malcolm Slaney (2013), "[Illinois] Neuroengineering IGERT Symposium: Three Projects to Understand the Cocktail Party Effect," http://nanohub.org/resources/18965.

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Time

Location

Beckman 1005, University of Illinois at Urbana-Champaign, Urbana, IL

Submitter

NanoBio Node, William Edward Nixon

University of Illinois at Urbana-Champaign

Tags

[Illinois] Neuroengineering IGERT Symposium: Three Projects to Understand the Cocktail Party Effect
by: Malcolm Slaney
  • Attention in the Machine: Three projects to understand the cocktail party effect 1. Attention in the Machine: Thre… 0
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  • The Problem 2. The Problem 67.310407790626911
    00:00/00:00
  • Binaural Workshop 3. Binaural Workshop 148.01452686252233
    00:00/00:00
  • Top-Down vs. Bottom-Up 4. Top-Down vs. Bottom-Up 222.64161662067846
    00:00/00:00
  • A Perceptual Problem 5. A Perceptual Problem 254.62465508845969
    00:00/00:00
  • Outline 6. Outline 531.87597809076681
    00:00/00:00
  • Real-time Attention Decoding with EEG 7. Real-time Attention Decoding w… 574.33107450089278
    00:00/00:00
  • EEG Approaches 8. EEG Approaches 608.6694530108748
    00:00/00:00
  • EEG Approaches 9. EEG Approaches 712.18044960233726
    00:00/00:00
  • Scientific Goal 10. Scientific Goal 827.71607693556234
    00:00/00:00
  • Project Decode 11. Project Decode 900.85558350917051
    00:00/00:00
  • Human Attention with ECoG 12. Human Attention with ECoG 972.87940269436785
    00:00/00:00
  • Decoding Approaches CCA Vespa 13. Decoding Approaches CCA Vespa 1141.5961288751826
    00:00/00:00
  • Decoding Speech 14. Decoding Speech 1248.5781528972568
    00:00/00:00
  • Attention Decoding vs. Window Size 15. Attention Decoding vs. Window … 1314.4037088135042
    00:00/00:00
  • Project Decode 16. Project Decode 1387.6671806524914
    00:00/00:00
  • Real-time Demo 17. Real-time Demo 1435.2698425580263
    00:00/00:00
  • Experimental Demo 18. Experimental Demo 1527.3760347346208
    00:00/00:00
  • Real-time Cocktail Party Analyzer 19. Real-time Cocktail Party Analy… 1632.1266839798734
    00:00/00:00
  • Attending to Conversations 20. Attending to Conversations 1704.5223989612075
    00:00/00:00
  • Scene Analysis Experiments 21. Scene Analysis Experiments 1798.7360006492452
    00:00/00:00
  • Why Model Attention? 22. Why Model Attention? 1856.2558837851
    00:00/00:00
  • Punting 23. Punting 1934.3540009738679
    00:00/00:00
  • Cognition Recognized Digits 24. Cognition Recognized Digits 1964.6015257263432
    00:00/00:00
  • Binaural Receiver 25. Binaural Receiver 2047.1623924687551
    00:00/00:00
  • ITD via a Silicon Cochlea 26. ITD via a Silicon Cochlea 2077.9057782827463
    00:00/00:00
  • Salience 27. Salience 2113.7317399772764
    00:00/00:00
  • Schematic 28. Schematic 2137.9049667261806
    00:00/00:00
  • ITD Histogram and Salience 29. ITD Histogram and Salience 2179.3093653627657
    00:00/00:00
  • Recognition 30. Recognition 2242.035789644538
    00:00/00:00
  • Cognition 31. Cognition 2256.0438646323651
    00:00/00:00
  • Results 32. Results 2296.456541145918
    00:00/00:00
  • Real-Time Movie 33. Real-Time Movie 2314.0596088297352
    00:00/00:00
  • Results 34. Results 2339.7204187631878
    00:00/00:00
  • Distracted 35. Distracted 2385.8354974841745
    00:00/00:00
  • Smart 36. Smart 2412.2400990099013
    00:00/00:00
  • Task Results 37. Task Results 2429.0993751014444
    00:00/00:00
  • Scene Analysis Engineering 38. Scene Analysis Engineering 2461.5782746307418
    00:00/00:00
  • Slide 39: Untitled 39. Slide 39: Untitled 2514.6354082129524
    00:00/00:00
  • Expected and 40. Expected and 2553.5605015419574
    00:00/00:00
  • Possible 41. Possible 2569.6759860412271
    00:00/00:00
  • EEG 42. EEG 2616.5348563544876
    00:00/00:00