Brett Y Smolenski

age ~52

from Utica, NY

Also known as:
  • Brett Y Snolenski

Brett Smolenski Phones & Addresses

  • Utica, NY
  • Pattersonville, NY
  • 2433 Forest Ln, Schwenksville, PA 19473
  • 2433 Forest Ln #E-8, Schwenksville, PA 19473
  • 6748 Stokes Westernville Rd #SS, Ava, NY 13303
  • Saint Petersburg, FL
  • Blue Bell, PA
  • Kissimmee, FL
  • Port Saint Lucie, FL
  • Montgomery, PA
  • PO Box 74, Schwenksville, PA 19473

Resumes

Brett Smolenski Photo 1

Lecturer

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Location:
Utica, NY
Industry:
Higher Education
Work:
North Point Defense, Inc
Senior Research Engineer

Assured Information Security (Ais) May 2012 - May 2017
Research Engineer

Suny Polytechnic Institute May 2012 - May 2017
Lecturer

Air Force Research Laboratory Jun 2001 - Aug 2001
Mathematics Consultant
Education:
Temple University 1999 - 2005
Doctorates, Doctor of Philosophy, Electronics Engineering, Philosophy
West Chester University of Pennsylvania 1999 - 2000
Masters, Master of Arts, Mathematics
Penn State University 1993 - 1996
Bachelors, Bachelor of Science, Electronics Engineering
Valencia College 1992 - 1993
Skills:
Matlab
Python
C (Programming Language
Linux
Pic Assembly
Ni Multisim
Brett Smolenski Photo 2

Brett Smolenski

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Us Patents

  • Method For Improving Speaker Identification By Determining Usable Speech

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  • US Patent:
    20050027528, Feb 3, 2005
  • Filed:
    Aug 18, 2004
  • Appl. No.:
    10/923157
  • Inventors:
    Robert Yantorno - Havertown PA, US
    Daniel Benincasa - Barneveld NY, US
    Stanley Wenndt - Rome NY, US
    Brett Smolenski - Schwenksville PA, US
  • International Classification:
    G10L019/02
  • US Classification:
    704246000
  • Abstract:
    Method for improving speaker identification by determining usable speech. Degraded speech is preprocessed in a speaker identification (SID) process to produce SID usable and SID unusable segments. Features are extracted and analyzed so as to produce a matrix of optimum classifiers for the detection of SID usable and SID unusable speech segments. Optimum classifiers possess a minimum distance from a speaker model. A decision tree based upon fixed thresholds indicates the presence of a speech feature in a given speech segment. Following preprocessing, degraded speech is measured in one or more time, frequency, cepstral or SID usable/unusable domains. The results of the measurements are multiplied by a weighting factor whose value is proportional to the reliability of the corresponding time, frequency, or cepstral measurements performed. The measurements are fused as information, and usable speech segments are extracted for further processing. Such further processing of co-channel speech may include speaker identification where a segment-by-segment decision is made on each usable speech segment to determine whether they correspond to speaker #1 or speaker #2. Further processing of co-channel speech may also include constructing the complete utterance of speaker #1 or speaker #2. Speech features such as pitch and formants may be extended back into the unusable segments to form a complete utterance from each speaker.

Youtube

:: good morning cephalgia ::

this is my senior thesis. yet another unfinished work...basically lack...

  • Category:
    Film & Animation
  • Uploaded:
    30 Jul, 2006
  • Duration:
    3m 39s

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