Initialization method for speech separation algorithms that work in the time-frequency domain.
This article addresses the problem of the unsupervised separation of speech signals in realistic scenarios. An initialization procedure is proposed for independent component analysis (ICA) algorithms that work in the time-frequency domain and require the prewhitening of the observations. It is shown that the proposed method drastically reduces the permuted solutions in that domain and helps to reduce the execution time of the algorithms. Simulations confirm these advantages for several ICA instantaneous algorithms and the effectiveness of the proposed technique in emulated reverberant environments.
Sarmiento
Auxiliadora
A
Departamento de Teoria de la Senal y Comunicaciones, University of Seville, Camino de los Descubrimientos S/N, 41092 Seville, Spain. sarmiento@us.es
Durán-Díaz
Iván
I
Cruces
Sergio
S
D000162:Acoustics / Q000295:instrumentation; D000465:Algorithms; D000669:Amplifiers, Electronic; D003198:Computer Simulation; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D013016:Sound; D013061:Speech Acoustics; D049250:Speech Recognition Software; D013997:Time Factors; D014159:Transducers; D014732:Vibration