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

Badlani, Rohan

Elizalde, Benjamin

Kumar, Anurag

Lane, Ian

Raj, Bhiksha

Shah, Ankit

Vincent, Emmanuel

English

arXiv

International audienceIn this paper we present our work on Task 1 Acoustic Scene Classification 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 0.48 compared to the baseline of 0.91

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Experiments on the DCASE Challenge 2016: Acoustic scene classification and sound event detection in real life recording

Experiments on the DCASE Challenge 2016: Acoustic Scene Classification
  and Sound Event Detection in Real Life Recording

Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording

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