When I first 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.
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
C++ Multithreading Cookbook in 2014 (publication year), that seems quite interesting, with all the new stuff from the current C++ standard. Is it what the book delivers?
Continue reading Book review: C++ Multithreading Cookbook
When I looked for an audio signal processing book, I found the classic DAFX: Digital Audio Effects, but the code is mainly Matlab. Was there a book with C++ examples? That’s how I found out about this book from Will Pirkle.
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
I’m happy to announce the release of a stereo compressor based on the Audio Toolkit. It is available on Windows and OS X (min. 10.8) in different formats. This stereo compressor can work on two channels, left/right or middle/side, possibly in linked mode (only one set of parameters), and can be set up to mix the input signal with the compressed signal (serial/parallel compression).
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!
Yet another book that my colleague suggested me to read. I also discussed it with another colleague who told me the same: this is a book that anyone in the oil and gas field should read. And what about people not in this industry?
I worked for a long time for the seismic department of my company, and switched to the reservoir department only last year. The problems that are tackled are quite different, and the way they are solved as well. So nothing to do with the book I reviewed a long time ago. So after 2 trainings in reservoir simulation, I also read this book that a colleague of mine labeled as the reference book.