Publication detail

Noise cancellation algorithms for speech signal distorted in telecommunication networks.

KOULA, I. ESPOSITO, A.

Original Title

Noise cancellation algorithms for speech signal distorted in telecommunication networks.

Type

conference paper

Language

English

Original Abstract

This paper aims to provide an evaluation of the effectiveness of three different speech noise power spectrum estimation algorithms The evaluation of their efficiency was based on the hit rate recognition obtained at the output of an HMM phoneme based speech recognizer. Noisy speech consisted of 100 speech sentences randomly extracted from the NTIMIT database. The best speech noise power spectrum estimator proved to be a procedure based on the arithmetic average of the power spectrums obtained from signal frames where no speech activity was detected. The noise spectrum estimate provide by either a four layer MLP neural network, or an Adaptive Neural Fuzzy Inference System (ANFIS) proved to give lower performance than the average noise spectrum estimator, even though both of them are able to detect some of the noise features and the ANFIS performance are better than those obtained from the MLP neural network.

Keywords

spectral subtraction, thresholdig, neural network, ANFIS, speech recognizer

Authors

KOULA, I.; ESPOSITO, A.

RIV year

2006

Released

1. 1. 2006

Publisher

Ústav radiotechniky a elektroniky, Akademie věd České republiky.

Location

česká republika, Praha

ISBN

86269-15-9

Book

16th Czech-German Workshop on speech processing

Pages from

1

Pages to

7

Pages count

7

BibTex

@inproceedings{BUT24891,
  author="Ivan {Koula} and Anna {Esposito}",
  title="Noise cancellation algorithms for speech signal distorted in telecommunication networks.",
  booktitle="16th Czech-German Workshop on speech processing",
  year="2006",
  pages="7",
  publisher="Ústav radiotechniky a elektroniky, Akademie věd České republiky.",
  address="česká republika, Praha",
  isbn="86269-15-9"
}