Detail publikace

Voice Activity Detection based-on Statistic Models

P. Sysel

Originální název

Voice Activity Detection based-on Statistic Models

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

voice activity detector statistical model

Autoři

P. Sysel

Rok RIV

2005

Vydáno

28. 9. 2005

Nakladatel

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

Místo

Prague, Czech Republic

ISBN

3-938863-17-X

Kniha

Proceedings of the 16th Conference Electronic Speech Signal Processing

Strany od

175

Strany do

180

Strany počet

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"
}