A pattern recognition approach to signal to noise ratio estimation of speech

Peter Adeyemi Awolumate, Mitchell Rudy, Ravi P. Ramachandran, Nidhal Carla Bouaynaya, Kevin D. Dahm, Rouzbeh Nazari, Umashanger Thayasivam

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

A blind approach for estimating the signal to noise ratio (SNR) of a speech signal corrupted by additive noise has been proposed. The method is based on a pattern recognition paradigm using various linear predictive based features, a vector quantizer classifier and estimation combination. Blind SNR estimation is very useful in biometric speaker identification systems in which a confidence metric is determined along with the speaker identity. It is also highly useful as a pre-processing step in speech and speaker recognition systems so that a proper degree of enhancement can be applied to augment system performance. This paper is a work in progress depicting the investigation conducted by two undergraduate students pertaining to (1) further research in SNR estimation and (2) the preparation of a laboratory manual to be used in an undergraduate class.

Original languageEnglish (US)
JournalASEE Annual Conference and Exposition, Conference Proceedings
Volume2017-June
StatePublished - Jun 24 2017
Event124th ASEE Annual Conference and Exposition - Columbus, United States
Duration: Jun 25 2017Jun 28 2017

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint

Dive into the research topics of 'A pattern recognition approach to signal to noise ratio estimation of speech'. Together they form a unique fingerprint.

Cite this