Title :
Informed Source Separation Using Iterative Reconstruction
Author :
Sturmel, Nicolas ; Daudet, Laurent
Author_Institution :
Inst. Langevin, Paris Diderot Univ., Paris, France
Abstract :
This paper presents a technique for Informed Source Separation (ISS) of a single channel mixture, based on the Multiple Input Spectrogram Inversion (MISI) phase estimation method. The reconstruction of the source signals is iterative, alternating between a time-frequency consistency enforcement and a re-mixing constraint. A dual resolution technique is also proposed, for sharper transients reconstruction. The two algorithms are compared to a state-of-the-art Wiener-based ISS technique, on a database of fourteen monophonic mixtures, with standard source separation objective measures. Experimental results show that the proposed algorithms outperform both this reference technique and the oracle Wiener filter by up to 3 dB in distortion, at the cost of a significantly heavier computation.
Keywords :
Wiener filters; audio coding; blind source separation; iterative methods; phase estimation; signal reconstruction; JPEG compression; MISI phase estimation method; Wiener-based ISS technique; audio source separation; dual resolution technique; informed source separation; iterative reconstruction; monophonic mixtures; multiple input spectrogram inversion phase estimation method; oracle Wiener filter; remixing constraint; single channel mixture; source signal reconstruction; standard source separation objective measures; time-frequency consistency enforcement; Convergence; Estimation; Quantization; Source separation; Spectrogram; Time frequency analysis; Transient analysis; Adaptive Wiener filtering; informed source separation; phase reconstruction; spectrogram inversion;
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
DOI :
10.1109/TASL.2012.2215597