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Star Analytical Services

Star Analytical Services

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Management Team

Joel M. MacAuslan
President & Chief Science Officer

Joel has served as a Scientist, Technical Consultant, and Program manager on both government and commercial contracts.  His work has included.

  • Mathematical and statistical analysis and customer presentations for tracking, signal, and imaging programs.
  • Logic analysis for safety certification of customer’s hardware-logic and software-driven equipment.
  • Design, testing, implementation, and evaluation of image-processing libraries for high-performance, “massively parallel” computing.
  • Mathematical and statistical analysis, algorithmic design for representation and computerized recognition of natural and spoken sounds. Project leader for a variety of research and development projects funded by the National Institutes of Health.
  • Project management, proposal development, personnel recruiting, strategic planning for projects analyzing complex (highly connected/high-feedback) systems.

Recent Publications

Boyce, S., J.MacAuslan, A. Bradlow, and R. Smiljanic.  2007. “Automatic Detection of Differences Between Clear & Conversational Speech”, ASHA Abstracts.

Boyce, S., J. MacAuslan, A. Bradlow, and R. Smiljanic.  2008.  “Landmark-based Analysis of Sleep Deprived Speech”, Proc. Acoustics 2008, Paris.  July.

Boyce, S., J. MacAuslan, W. Carr, D. Picchioni, A. Braun, and T. Balkin.  2008.  “Automatic Detection of Changes in Speech Clarity during Sleep Deprivation”, Proc. SLEEP, Baltimore .  June.

Dai K.,H. Fell, and J. MacAuslan.  2008.  “Recognizing Emotion in Speech Using Neural Networks”, Proc. IASTED 2008 on Assistive Technologies, ACTA Press 2008.

Chenausky, Karen, Joel MacAuslan and Richard Goldhor.  2011.  “Acoustic Analysis of PD Speech”, Parkinson’s Disease, vol. 2011, Article ID 435232, 2011.

Boyce, Suzanne, H. Fell, L. Wilde, & J. MacAuslan.  2011.  “Automated Tools for Identifying Syllabic Landmark Clusters that Reflect Changes in Articulation”, Proc. MAVEBA, Florence, Italy. August.

Goldhor, Richard; Keith Gilbert; Joel MacAuslan; Karen Payton.  2011.  “Only Mostly Blind Source Separation”, Signal Processing in Medicine and Biology Symposium (SPMB), 2011 IEEE. doi:10.1109/SPMB.2011.6120109.

Smith, S.M., Joel MacAuslan, Richard Goldhor, Karen Chenausky, Ryan A. Coute, Richard W. Barus, and Howard A. Smithline.  2012.  “Using acoustic analysis of coughs to identify respiratory infections in the emergency department”, Pres. Society for Academic Emergency Medicine Annual Meeting, May 2012. Chicago IL.

Patents
 
J.MacAuslan.  Determining a tangent space and filtering data onto a manifold, US 7,124,065.

J.MacAuslan, V. Chari , R.Goldhor, and C. Espy-Wilson.  Electrolaryngeal Speech Enhancement for Telephony , US6,975,984.

J.MacAuslan.  Detecting a Physiological State Based on Speech , US applic. #  11/835,990 (pending).

J.MacAuslan. Cough Analysis, US applic. # 12/886,363 (pending).

R. Goldhor, K. Gilbert, J. MacAuslan, and K. Payton. Signal Source Separation, # 61/666,696 (pending).

 
Education

Michigan State University, MI,
Michigan State University, MI,
Cornell University, NY,
Cornell University, NY
B.S.
M.S.
M.S.
Ph. D.
1973, Astrophysics
1975, Applied Mathematics
1979, Astrophysics
1981, Astrophysics

Primary Sidebar

Clarity in Motion

Listeners with hearing problems find noisy rooms, such as many classrooms, burdensome because speech is hard to understand in rooms with multiple interfering sound sources.  Existing methods of extracting or suppressing individual sounds generally require that those sounds be motionless—that is, that the sound source remains stationary. We are developing a hearing aid-compatible system capable of extracting or suppressing the sound of moving sources.

This system would use multiple microphones in a classroom or other space where people gather.  It would isolate individual sound sources such as speech, removing unwanted noise and separating sounds of interest even in situations in which sound sources moved in arbitrary ways.  Then it would deliver enhanced speech or other signals to the ears of multiple listeners in the room, personalized to each listener, via their cellphones and preferred listening devices.

Click here for an example. 

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