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Dergiler / International Journal of Applied Mathematics Electronics and Computers / 2016 / Special Issue (2016)

Speech Denoising using Common Vector Analysis in Frequency Domain

Erol Seke
Mehmet Hakan Durak
Kemal Özkan
Sayfa
224–229
Yayın Tarihi
2016-12-01
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Results are compared with that of the state of the art in well-known speech quality measures.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Signal denoising approaches on data of any dimension largely relies on the assumption that data and the noise components and the noise itself are somewhat uncorrelated.
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Temel Bulgular & Veri:Therefore, several proposed algorithms try to separate the data into two or more parts with varying noise levels so that denoising process can be applied on them with different parameters and constraints.
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Sonuç & Katkı:Results are compared with that of the state of the art in well-known speech quality measures.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:speech · denoising · Common Vector Analysis

Abstract

Signal denoising approaches on data of any dimension largely relies on the assumption that data and the noise components and the noise itself are somewhat uncorrelated. However, any denoising process heavily depending on this assumption retreats when the signal component is adversely affected by the operation. Therefore, several proposed algorithms try to separate the data into two or more parts with varying noise levels so that denoising process can be applied on them with different parameters and constraints. In this paper, the proposed method separates the speech data into magnitude and phase where the magnitude part is further separated into common and difference parts using common vector analysis. It is assumed that the noise largely resides on difference part and therefore denoised by a known algorithm. The speech data is reconstructed by combining common, difference and phase parts. Using Linear Minimum Mean Square Error Estimation algorithm on the difference part, excellent denoising results are obtained. Results are compared with that of the state of the art in well-known speech quality measures.

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Bu Makaleye Atıf Yap

Seke, E., Durak, M. H., Özkan, K. (2016). Speech Denoising using Common Vector Analysis in Frequency Domain. International Journal of Applied Mathematics Electronics and Computers, Special Issue (2016), 224–229. https://ajindex.com/articles/258188

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Kaynakça (8)

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