Kaggle In-Class competition on acoustic scene classification

We have launched a Kaggle in Class competition on acoustic scene classification as part of TUT course (SGN-41007 Pattern Recognition and Machine Learning.). Competition is open for everybody whether you are participating the TUT course or not.

The competition data is similar to DCASE2017 Task 1 data, audio material from 15 scene classes split into 10-second segments. Contrary to the DCASE2107, were audio signals were released, only acoustic feature matrices (mel-energies) extracted for the audio signals are released. This shifts the research focus more on the machine learning side of the problem and makes the problem more approachable to the Kaggle community.