There are several different low pass filters, and as many high pass, band pass, band stop… filters. In Audio toolkit, there are different usual implementation available:
- Chebyshev type 1
- Chebyshev type 2
- Second order
and it is possible to implement other, different orders as well…
Continue reading Audio Toolkit: Different low pass 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.
Continue reading Announcement: Audio TK 0.7.0
When I first read about transient shaper, I was like “what’s the difference with a compressor? Is there one?”. And I tried to see how to get these transient without relying on the transient energy, with a relative power (ratio between the instant power and the mean power) filter, or its derivative, but nothing worked. Until someone explained that the gain was driven by the difference between a fast attack filtered power and a slower one. So here it goes.
Continue reading Audio Toolkit: Anatomy of a transient shaper
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).
Continue reading Announcement: Audio TK 0.6.0
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://blog.audio-tk.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!
I’d like to talk a little bit about the way a compressor and an expander can be written with the Audio Toolkit. Even if both effects use far less filters than the SD1 emulation, they still implement more than just one filter in the pipeline, contrary to a fixed delay line (another audio plugin that I released with the compressor and the expander).
Continue reading Audio Toolkit: ATKCompressor and ATKExpander Implementation
A lot has happened in two weeks for Audio ToolKit. This release mainly adds tools for Compressor and Delays design. There will be additional plugins release soon.
Continue reading Announcement: Audio TK 0.4.0
Just after the release of ATK SD1, I updated my audio toolkit. I added a few optimizations on overdrive computations, and also for the base filter array exchange.
Continue reading Announcement: Audio TK 0.3.0
It’s time for a new release of the toolkit. Much has been done in terms of basic filters, but also to simplify usage (static and shared libraries are compiled, no need to reset the pipeline before calling process…).
Continue reading Announcement: Audio TK 0.2.0