In this paper we present our work on Task 1 Acoustic Scene Classi- fication and Task 3 Sound Event Detection in Real Life Recordings. Among our experiments we have low-level and high-level features, classifier optimization and other heuristics specific to each task. Our performance for both tasks improved the baseline from DCASE: for Task 1 we achieved an overall accuracy of 78.9% compared to the baseline of 72.6% and for Task 3 we achieved a Segment-Based Error Rate of 0.76 compared to the baseline of 0.91.
@article{arxiv.1607.06706,
title = {Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording},
author = {Benjamin Elizalde and Anurag Kumar and Ankit Shah and Rohan Badlani and Emmanuel Vincent and Bhiksha Raj and Ian Lane},
journal= {arXiv preprint arXiv:1607.06706},
year = {2016}
}