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  • ElecEng
  • GC-ElecEng 2021
  • 63.Cnf-1179
ElecEng Congresses with Published Papers
GC-ElecEng 2020, Valencia
2
GC-ElecEng 2021, Valencia
5
Papers Published at GC-ElecEng 2021
All 5 Papers
IDAuthors and TitlePages
43.Cnf-38 Mr. Aron Kondoro
Ms. Diana Rwegasira
Prof. Imed Dhaou
Prof. Hannu Tenhunen
Trends of using blockchain technology in the smart grid
1-7
63.Cnf-75 Mr. Andres Rojas
Prof. Gordana J. Dolecek
Evaluation of Supervised Machine Learning Classification Algorithms for Fingerprint Recognition
8-11
62.Cnf-106 Mr. Joan Carles Montero
Ms. Merce Feliu
Dr. Joan Bas
Optical Communications Through Low Orbit Satellites
12-17
63.Cnf-140 Dr. Mohammad Al-Mousa
Mr. Nael Sweerky
Dr. Ghassan Samara
Dr. Mohammed Alghanim
Ms. Abla Hussein
Mr. Braa Qadoumi
General Countermeasures of Anti-Forensics Categories
18-23
62.Cnf-143 Dr. Ghassan Samara
Mr. Mohammad Hussein
Dr. Khalid Alqawasmi
Alarm System at street junctions (ASSJ) to avoid accidents Using VANET system
24-28
63.Cnf-1179 Paper View Page
Title Speech Noise Reduction with Wavelet Transform Domain Adaptive Filters
Authors Ms. Elif Özen, Yaşar Üniversitesi, Izmir, Turkey
Dr. N Ozkurt, Yaşar Üniversitesi, Izmir, Turkey
Abstract Adaptive filters are one of the most promising solutions to several signal enhancement problems in a non-stationary environment. However, depending on the characteristics of the signals and noise, the processing complexity and convergence speed for adaptive filters vary. Therefore, it is often preferred to apply adaptive filters in the transform domain to reduce complexity and increase convergence speed. In this paper, the application of the LMS (Least Mean Square) algorithm, which is the most preferred algorithm of adaptive filters in the field of speech noise cancellation, in the wavelet transform domain was studied. For this purpose, improving speech signals with different Signal to Noise Ratio (SNR) using Wavelet Transform Domain LMS (WTD-LMS) algorithm in the proposed method was applied. The results obtained were evaluated with measures that are frequently used in speech enhancement applications. It is observed that the success of the proposed method outperforms adaptive and traditional methods for two sensor measurements are available.
Track Speech: Digital Speech and Audio Processing
Conference 2nd Mosharaka International Conference on Digital Signal Processing (MIC-Signals 2021)
Congress 2021 Global Congress on Electrical Engineering (GC-ElecEng 2021), 10-12 December 2021 (Remotely), Valencia, Spain
Pages --1
Topics Digital Speech Processing
Speech Enhancement
ISSN 2227-331X
DOI
BibTeX @inproceedings{1179ElecEng2021,
title={Speech Noise Reduction with Wavelet Transform Domain Adaptive Filters},
author={Elif Özen, and N Ozkurt},
booktitle={2021 Global Congress on Electrical Engineering (GC-ElecEng 2021)},
year={2021},
pages={--1},
doi={}},
organization={Mosharaka for Research and Studies} }
Paper Views 154 Paper Views Rank 244/525
Paper Downloads 76 Paper Downloads Rank 247/525
GC-ElecEng 2021 Visits: 75301||MIC-Signals 2021 Visits: 9006||Speech Track Visits: 1068