Introducing Undergraduates to Pattern Recognition and Machine Learning through Speech Processing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper describes an educational project experience that achieves a software implementation and performance analysis of a blind signal to noise ratio (SNR) estimation system for noisy speech. The system is based on a pattern recognition paradigm and no clean speech reference signal is available. It is a product of the faculty's research and funded by a government contract. The faculty's research on a real-world issue in speech processing has been converted into an undergraduate project. Assessment results show that the project is viewed very favorably by students. Target versus control group results show that the target group feels better qualified for graduate study and career options in digital signal processing.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7635-7639
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: May 12 2019May 17 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period5/12/195/17/19

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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