Identification of acoustic MIMO systems: challenges and opportunities
Signal Processing
EURASIP Journal on Applied Signal Processing
Performance of GCC-and AMDF-based time-delay estimation in practical reverberant environments
EURASIP Journal on Applied Signal Processing
Time delay estimation in room acoustic environments: an overview
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Advances in Signal Processing
A two microphone-based approach for source localization of multiple speech sources
IEEE Transactions on Audio, Speech, and Language Processing
Real-time joint blind speech separation and dereverberation in presence of overlapping speakers
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
A real-time speech enhancement framework for multi-party meetings
NOLISP'11 Proceedings of the 5th international conference on Advances in nonlinear speech processing
Real-Time speech recognition in a multi-talker reverberated acoustic scenario
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Dominance detection in a reverberated acoustic scenario
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Conversational speech recognition in non-stationary reverberated environments
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Blind single channel identification based on signal intermittency and second-order statistics
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Structured Sparsity Models for Reverberant Speech Separation
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Hi-index | 35.68 |
We extend our previous studies on adaptive blind channel identification from the time domain into the frequency domain. A class of frequency-domain adaptive approaches, including the multichannel frequency-domain LMS (MCFLMS) and constrained/unconstrained normalized multichannel frequency-domain LMS (NMCFLMS) algorithms, are proposed. By utilizing the fast Fourier transform (FFT) and overlap-save techniques, the convolution and correlation operations that are computationally intensive when performed by the time-domain multichannel LMS (MCLMS) or multichannel Newton (MCN) methods are efficiently implemented in the frequency domain, and the MCFLMS is rigorously derived. In order to achieve independent and uniform convergence for each filter coefficient and, therefore, accelerate the overall convergence, the coefficient updates are properly normalized at each iteration, and the NMCFLMS algorithms are developed. Simulations show that the frequency-domain adaptive approaches perform as well as or better than their time-domain counterparts and the cross-relation (CR) batch method in most practical cases. It is remarkable that for a three-channel acoustic system with long impulse responses (256 taps in each channel) excited by a male speech signal, only the proposed NMCFLMS algorithm succeeds in determining a reasonably accurate channel estimate, which is good enough for applications such as time delay estimation.