Hi -I don't have any source code for you, I'm afraid. But if you take the envelopes of the two signals, then for each of your candidate time-delays you have a set of 2D data points (use the same number of points for each time-delay). There are various ways to estimate the mutual information from that, then you just look for the time-delay giving the largest mutual information.
The quick and dirty way to get a MI value is to calculate a 2D histogram and the two corresponding 1D histograms (representing the marginals of the 2D histogram) and calculate the mutual information from the entropies of those 3 distributions (I(X;Y) = H(X) + H(Y) - H(X,Y)). This is a rough approach but easy and quick. There are various tweaks you could add such as adaptive bin widths etc.
There are more accurate approaches. One is:Estimation of the information by an adaptive partitioning of the observation space
Darbellay and Vajda (1999) http://dx.doi.org/10.1109/18.761290I'm not much of a vision person but I believe MI is used for image alignment fairly often - a very similar task. It's discusse in this paper (which also describes another approach to the estimation, using Nearest-Neighbours):
High-Dimensional Entropy Estimation for Finite Accuracy Data: R-NN Entropy Estimator
Kybic (2007) http://dx.doi.org/10.1007/978-3-540-73273-0_47 HTH Dan Dermot Campbell wrote:
Hi Dan, Im also interested in this. Do you have any more information on what you proposed or even source code? Thanks, Dermot. ------------------------------------------------ Dermot Martin Campbell, Postgraduate Research Student, Dept. of Electronic Eng., National University of Ireland, Galway City. Tel:(091) 493031 Email: Dermot.Campbell@xxxxxxxxxxxxHi - You might like to consider using mutual information as an alternative to cross-correlation. The advantage is that cross-correlation is always about the linear dependencies between the signals, whereas the mutual information can also highlight nonlinear dependencies (for example, in your case, the codec may have added compression). Dan Junyong You wrote:Hi John and all, In fact, I am also looking for the time alignment of two samples, one is the original, and another is decoded. My problem is to estimate the time delay caused by audio coding. I try a classifical estimation method, which makes use of envelope based cross-correlation function. That means, the envelopes of two samples are computed firstly, and then calculate the cross correlation function of these two envelopes, and then select the time length corresponding to the maximal correlation as the delay. I hope this method will help you, and if anyone has better approaches, please let me know, thank you very much. BR, Junyong You TUT, Finland ----- Original Message ----- From: John Spencer To: AUDITORY@xxxxxxxxxxxxxxx Sent: Wednesday, July 02, 2008 2:11 PM Subject: [AUDITORY] Audio Time and/or Level Alignment Algorithm Hello List, I am looking for advice and help with a problem. I have 2 audio signals each recorded in different environments but both are the same length. I need to align them the best I can or align at leats one of them to match the other. They need to be aligned time wise and level wise if possible. Any advice appreciated, thanks. John Spencer ------------------------------------------------------------------------------ Walla! Mail - Get your free unlimited mail today-- Dan Stowell Centre for Digital Music Queen Mary, University of London Mile End Road, London E1 4NS http://www.elec.qmul.ac.uk/department/staff/research/dans.htm http://www.mcld.co.uk/
-- Dan Stowell Centre for Digital Music Queen Mary, University of London Mile End Road, London E1 4NS http://www.elec.qmul.ac.uk/department/staff/research/dans.htm http://www.mcld.co.uk/