Publication detail

Voice Activity Detection based-on Statistic Models

P. Sysel

Original Title

Voice Activity Detection based-on Statistic Models

Type

conference paper

Language

English

Original Abstract

This paper deals with the method of voice activity detection. Rising requirements to applications with variable-rate speech coding also increases the role of voice activity detectors which become crucial for the efficient bandwidth reduction. The paper aims especially to two detector types; these are the detector based on short-time signal energy and statistical model-based voice activity detector. Decision-making rules of the statistical model-based detector are derived from the LRT (Likelihood Ratio Test) by estimating unknown parameters using the ML (Maximum Likelihood) criterion. In addition there is an effective hang-over scheme based on HMM (Hidden Markov Model) principles in the detector. There were models for these detectors created in Matlab simulation environment. Models were tested on voice signals with the white noise as well as real noises. The results were evaluated and compared for various types of noises and SNR (Signal to Noise Ratios) values.

Keywords

voice activity detector statistical model

Authors

P. Sysel

RIV year

2005

Released

28. 9. 2005

Publisher

Academy of Science of the Czech Republic, Institute of Radio Engineering and Electronics

Location

Prague, Czech Republic

ISBN

3-938863-17-X

Book

Proceedings of the 16th Conference Electronic Speech Signal Processing

Pages from

175

Pages to

180

Pages count

6

BibTex

@inproceedings{BUT15215,
  author="Petr {Sysel}",
  title="Voice Activity Detection based-on Statistic Models",
  booktitle="Proceedings of the 16th Conference Electronic Speech Signal Processing",
  year="2005",
  pages="6",
  publisher="Academy of Science of the Czech Republic, Institute of Radio Engineering and Electronics",
  address="Prague, Czech Republic",
  isbn="3-938863-17-X"
}