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SES PARMAKİZİ
Hakan Akgün 040080475
Metehan Corut 040080470
Duygu Mumci 040090947
Danışman Hoca: Serap Kırbız
İçerik:
 Sonuçlar
 Algoritma
o Özniteliklerin Elde Edilmesi
o Veritabanının Oluşturulması
o Eşleştirme
 Giriş
o Ses tanıma nedir?
o Ne İşe Yarar?
Giriş
??
Ses Tanıma Nedir?
 İki sesin birbirinin aynısı olup olmadığını
belirleyen işlem.
Ne İşe Yarar?
 Radyoda çalan şarkının bulunması
 Alternatif güvenlik sistemi kurulması
Algoritma
1) Özniteliklerin Bulunması
 Veri tabanının oluşturulması
2) Eşleştirme
Öznitelikler
 Sıfır geçiş sayısı
 Enerji
 Mel Frekansı Kepstral Katsayıları
 Karekök Ortalama
 Fourier Katsayıları
Karekök Ortalama (RMS)
 {x1, x2, ... , xn} değerleri için RMS:
Sıfır Geçiş Oranı (Zero Cross Rate)
MFCC (Mel-Frequency
Cepstrum Coeffiecients)
 Bir sesin kısa süreli güç spektrumu gösterimi
 Fourier Dönüşümü
 Üçgen pencereleme
 Her değerin logaritmasının alınması
 Kosinüs Dönüşümü
Özniteliklerin Elde Edilmesi
Örnekleme frekansının 44100 Hz ‘ten 8000 Hz’e düşürülmesi
Spectrogram ile pencerelere ayırma işlemi
Her pencere için istenilen özniteliğin hesaplanması
Elde edilen verilerin dosyalara kaydedilmesi
Ses İşareti
Şarkı
1.
Öznitelik
Değerler
2.
Öznitelik
Değerler
3.
Öznitelik
Değerler
Veritabanı
Eşleştirme
Örnek sesin özniteliklerinin
elde edilmesi
Veritabanındaki
değerlerle
karşılaştırılması
Bulunan Şarkı
Karşılaştırma
 Örnek işaretin öznitelik değerlerinin
veritabanındaki değerlerle olan farkı
bulunur.
 Her öznitelik için farkın en düşük olduğu
şarkının istenilen şarkı olduğuna karar
verilir.
Sonuç
 Başarı oranının bağlı olduğu etkenler:
1. Gürültü
2. Özniteliklerin gürbüz olması
3. Veritabanındaki şarkı sayısı
4. Kayıt yapılan ortam
5. Kayıt için kullanılan cihazlar

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