Vector quantization and signal compression
Vector quantization and signal compression
Computational auditory scene analysis
Computational auditory scene analysis
Blind Source Separation by Sparse Decomposition in a Signal Dictionary
Neural Computation
Separating more sources than sensors using time-frequency distributions
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Harmonic decomposition of audio signals with matching pursuit
IEEE Transactions on Signal Processing
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
Underdetermined Blind Separation of Nondisjoint Sources in the Time-Frequency Domain
IEEE Transactions on Signal Processing
Performance measurement in blind audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Sparse and structured decompositions of signals with the molecular matching pursuit
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Information Theory
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Informed source separation using latent components
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
An adaptive robust watermarking algorithm for audio signals using SVD
Transactions on computational science X
Informed source separation through spectrogram coding and data embedding
Signal Processing
A blind digital audio watermarking scheme based on EMD and UISA techniques
Multimedia Tools and Applications
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In this paper, the issue of audio source separation from a single channel is addressed, i.e., the estimation of several source signals from a single observation of their mixture. This challenging problem is tackled with a specific two levels coder-decoder configuration. At the coder, source signals are assumed to be available before the mix is processed. Each source signal is characterized by a set of parameters that provide additional information useful for separation. We propose an original method using a watermarking technique to imperceptibly embed this information about the source signals into the mix signal. At the decoder, the watermark is extracted from the mix signal to enable an end-user who has no access to the original sources to separate these signals from their mixture. Hence, we call this separation process informed source separation (ISS). Thereby, several instruments or voice signals can be segregated from a single piece of music to enable post-mixing processing such as volume control, echo addition, spatialization, or timbre transformation. Good performances are obtained for the separation of up to four source signals, from mixtures of speech or music signals. Promising results open up new perspectives in both under-determined source separation and audio watermarking domains.