Adaptive blind separation of independent sources: a deflation approach
Signal Processing
A fast fixed-point algorithm for independent component analysis
Neural Computation
Extraction of Specific Signals with Temporal Structure
Neural Computation
IEEE Transactions on Neural Networks
Source separation using single channel ICA
Signal Processing
ECG compression by efficient coding
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Speech enhancement based on the response features of facilitated EI neurons
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
| Hi-index | 0.08 |
A number of approaches have been proposed for enhancing/extracting a given speech in a noisy environment, in the aim of, for example, enhancing the speech recognition rate. The speech enhancement can be carried out by either using single or multiple channel measurements. Some of those approaches explore the harmonicity of speech, and others make use of the redundancy among the channels, usually by independent component analysis. To enhance one speech from a single channel, we propose here to use the characteristics of speech through the concept of efficient coding, which mimics the way the auditory cortex code information. This is carried out in a supervized fashion. Simulations and real world measurements show that this technique can be used efficiently to enhance a given speech signal.