AUDIO SIGNAL SEPERATION WITH SINGLE CHANNEL BLIND SOURCE SEPERATION

Year 2019, Volume: 14 Issue: 1, 26 - 38, 31.01.2019

Hüsamettin Çelik , Fatih Yavuz Ilgın , Yusuf Sevim

Abstract

      Blind source separation
can be defined as estimating each source that makes up this mixture from a data
set containing a mixture of more than one signal. Calling this process as blind
specifies that there is no additional information about resources. Since it has
as many signals as the number of signals to be estimated on the blind source separation,
estimating sources is a cost process because of there is only one mixing signal
on the single-channel blind source separation process. An unwanted noise
attached to any signal can be separated from the source signal thanks to said
method. Similarly two different instrumental signal sources recorded with a
single microphone can be separated from each other as in this study. In this
study, two signals recorded as single channel were separated from each other
with non-negative matrix separation using continuous wavelet transform. The
results were evaluated in terms of signal noise ratio and signal distortion
ratio to evaluate the performance analysis of the proposed method. 

Keywords

Blind Source Separation, Cocktail Party Problem, Non-Negative Matrix Factorization, Continuous Wavelet Transform

MÜZİK İŞARETLERİN TEK KANAL KÖR KAYNAK AYRIŞTIRMA İLE AYRIŞTIRILMASI

Abstract

Kör kaynak ayrıştırma, birden fazla sinyalin
karışımını içeren bir veri kümesinden bu karışımı oluşturan her bir kaynağın
tahmin edilmesi olarak tanımlanabilir. Bu işlemin kör olarak adlandırılması
kaynaklar hakkında hiçbir ek bilgi olmadığını belirtmektedir. Kör
kaynak ayrıştırma da tahmin edilecek sinyal sayısı kadar karışım sinyali
varken, tek kanal kör kaynak ayrıştırma işleminde sadece bir karışım sinyali
olduğundan kaynakların tahmini maliyetli bir işlemdir. Bahsedilen bu yöntemle
herhangi bir işarete eklenmiş istenmeyen bir gürültü kaynak işaretinden
ayrıştırılabilir. Benzer şekilde bu çalışmada olduğu gibi tek bir mikrofonla
kaydedilmiş 2 farklı enstrümantal işaret kaynağı birbirinden ayrıştırılabilir.
Yapılan bu çalışmada sürekli dalgacık dönüşümü kullanılarak negatif olmayan
matris ayrıştırma ile tek kanallı olarak kaydedilen iki işaret birbirinden
ayrıştırılmıştır. Önerilen yöntemin başarım analizini değerlendirmek için sonuçlar
işaret gürültü oranı ve işaret bozulma oranı cinsinden
değerlendirilmiştir. 

Keywords

Kör Kaynak Ayrıştırma, Negatif Olmayan Matris Ayrıştırma, Sürekli Dalgacık Dönüşümü, Kokteyl Parti Problemi, Sürekli Dalgacık Dönüşümü

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