Early abductive reasoning for blind signal separation
Başlık çevirisi mevcut değil.
- Tez No: 508146
- Danışmanlar: Prof. S. HAMİD NAWAB
- Tez Türü: Doktora
- Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Elektrik ve Elektronik Mühendisliği, Computer Engineering and Computer Science and Control, Electrical and Electronics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2017
- Dil: İngilizce
- Üniversite: Boston University
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 149
Özet
Özet yok.
Özet (Çeviri)
We demonstrate that explicit and systematic incorporation of abductive reasoning capabilities into algorithms for blind signal separation can yield significant performance improvements. Our formulated mechanisms apply to the output data of signal processing modules in order to conjecture the structure of time-frequency interactions between the signal components that are to be separated. The conjectured interactions are used to drive subsequent signal separation processes that are as a result less blind to the interacting signal components and, therefore, more effective. We refer to this type of process as early abductive reasoning (EAR); the“early”refers to the fact that in contrast to classical Artificial Intelligence paradigms, the reasoning process here is utilized before the signal processing transformations are completed. We have used our EAR approach to formulate a practical algorithm that is more effective in realistically noisy conditions than reference algorithms that are representative of the current state of the art in two-speaker pitch tracking. Our algorithm uses the Blackboard architecture from Artificial Intelligence to control EAR and advanced signal processing modules. The algorithm has been implemented in MATLAB and successfully tested on a database of 570 mixture signals representing simultaneous speakers in a variety of real-world, noisy environments. With 0 dB Target-to-Masking Ratio (TMR) and no noise, the Gross Error Rate (GER) for our algorithm is 5% in comparison to the best GER performance of 11% among the reference algorithms. In diffuse noisy environments (such as street or restaurant environments), we find that our algorithm on the average outperforms the best reference algorithm by 9.4%. With directional noise, our algorithm also outperforms the best reference algorithm by 29%. The extracted pitch tracks from our algorithm were also used to carry out comb filtering for separating the harmonics of the two speakers from each other and from the other sound sources in the environment. The separated signals were evaluated subjectively by a set of 20 listeners to be of reasonable quality.
Benzer Tezler
- Les inégalités et les variations dans la profession d'avocat : une étude sur la socialisation professionnelle et les trajectoires des jeunes avocats
Avukatlık mesleğinde eşitsizlikler ve varyasyonlar: Genç avukatların mesleki sosyalizasyonu ve kariyer yolları üzerine bir araştırma
FURKAN ESEN
Yüksek Lisans
Fransızca
2024
SosyolojiGalatasaray ÜniversitesiSosyoloji Ana Bilim Dalı
DOÇ. DR. KAMİL CEM ÖZATALAY
- Evli bireylerde aile huzuru, öfke tarzları ve erken dönem uyum bozucu şemalar arasındaki ilişki
The relationship between family peace, angry styles and early addictive schemes in married individuals
ALİ EREN YILDIZ
Yüksek Lisans
Türkçe
2023
Psikolojiİstanbul Aydın ÜniversitesiPsikoloji Ana Bilim Dalı
DR. ÖĞR. ÜYESİ KAHRAMAN GÜLER
- Erken cumhuriyet Döneminde tütün bağımlılığı
Tobacco addiction in the Early R0epublican Period
ÇİLEM KURT
- Narrating ravishment in early modern English literature
Erken modern dönem İngiliz edebiyatında ravishment anlatısı
FİRDEVS İDİL KURTULAN
Yüksek Lisans
İngilizce
2022
İngiliz Dili ve EdebiyatıBoğaziçi ÜniversitesiBatı Dilleri ve Edebiyatları Ana Bilim Dalı
DR. ÖĞR. ÜYESİ ETHAN JOHN GUAGLIARDO
- Ergenlik dönemindeki benlik saygısı ile sigara bağımlılığı arasındaki ilişkinin incelenmesi
Researching of the relationship between self-esteem and smoking addiction during adolesence
ZÜHAL TUNÇ
Yüksek Lisans
Türkçe
2019
Psikolojiİstanbul Aydın ÜniversitesiPsikoloji Ana Bilim Dalı
YRD. DOÇ. DR. ŞAHİDE GÜLİZ KOLBURAN