After my transient shaper, some people told me it would be nice to have a splitter: split the signal in two tracks, one with the transient, another with the sustain. For instance, it would be interesting to apply a different distortion on both signals.
ATK is updated to 1.3.0 with new features and optimizations.
I’ve decided to create a real space for Audio ToolKit. The idea is to make it more visible, with a consistent message to the users.
In addition to this move, this blog has move to a subdomain there (and you may have noticed it) and Audio ToolKit documentation as well.
This is mainly a bug fix release. A nasty bug on increasing processing sizes would corrupt the input data and thus change the results. It is advised to upgrade to this release as soon as possible.
This is the first stable release of the Audio Toolkit, after more than a year of development. In addition to the serial pipeline, there is now an option to use TBB to render each chunk in parallel. The pipeline can also return the maximum latency the pipeline possesses if all latency information is given during the build of the pipeline.
Additional filters were also added to complement the current set of filters.
Focus on this release was on performance. As such the core functions were optimized, as well as some tools and EQ.
A new filter dedicated to fast convolution (using a fixed-size partition with a mix of FFT convolution and explicit FIR filter) with 0 latency was added.
The main changes for this release are first trials at modulated filters, C++11 usage (nullptr, override and final), and some API changes (the main process_impl function is now const).
Sometimes images are worth a thousand words, so let’s look at some pictures of a middle-side compressor behavior.
Continue reading Audio Toolkit: Anatomy of a middle-side compressor
There are now a few books on sickit-learn, for instance a general one on machine learning systems, and a cookbook. I was a technical reviewer for the first one, and now I’m reviewing the cookbook.
Continue reading Book review: scikit-learn Cookbook
Almost 18 months ago, I posted a small post on the first version of this book (http://matt.eifelle.com/2013/09/04/book-building-machine-learning-systems-in-python/). At the time, I was really eager to see the second edition of it. And there it is!
I had once again the privilege of being a technical reviewer for this book, and I havce to say that the quality didn’t lower one bit, it went even higher. Of course, there is still room for a better book, when all Python module for Machine Learning are even better. I guess that will be for the third edition!
To get the book from the publisher: https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-systems-python-second-edition
On other matters, the blog was quiet for a long time, I’m hoping to get some time to post a few new posts soon, but it is quite hard as I’m currently studying for another master’s degree!