Introducing openSMILE 3.0
We are happy to announce the availability of the next major release 3.0 of openSMILE, audEERING’s open-source, cross-platform audio feature extractor. With more than 150,000 downloads since its first publication in 2010 and more than 2650 citations in academic papers, openSMILE has become an immensely popular tool among the research community, audio-related companies and individuals. We strongly believe that researchers and enthusiasts should have free and unrestricted access to the fundamental tools that they need for their work and to make new advances in these fields.
Know Your Data – Using Compressed Audio with Machine Learning Applications
Data collection is an important issue in machine learning research. If we use YouTube as a resource do we really know what we are getting? To that end do we really know what’s in our audio data?