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KOULA, I. ESPOSITO, A.
Originální název
Noise cancellation algorithms for speech signal distorted in telecommunication networks.
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
spectral subtraction, thresholdig, neural network, ANFIS, speech recognizer
Autoři
KOULA, I.; ESPOSITO, A.
Rok RIV
2006
Vydáno
1. 1. 2006
Nakladatel
Ústav radiotechniky a elektroniky, Akademie věd České republiky.
Místo
česká republika, Praha
ISBN
86269-15-9
Kniha
16th Czech-German Workshop on speech processing
Strany od
1
Strany do
7
Strany počet
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" }