· 2015
ESC
- 1,360citations
- 2015year
Short summary
A new dataset of 2,000 annotated environmental sound clips (50 classes) and 250,000 unlabeled excerpts addresses the scarcity of public data for sound classification research.
AI-generated from the title and abstract; the full text is not read.
Key points
- Presents a new dataset with 2,000 annotated environmental sound clips across 50 classes.
- Includes an additional 250,000 unlabeled auditory excerpts from the Freesound project.
- Addresses the scarcity of publicly available datasets for environmental sound classification research.
- Evaluates human accuracy in classifying environmental sounds.
- Compares human performance to baseline classifiers using MFCC and zero-crossing rate features.
AI-generated from the title and abstract; the full text is not read.
Abstract
One of the obstacles in research activities concentrating on environmental sound classification is the scarcity of suitable and publicly available datasets. This paper tries to address that issue by presenting a new annotated collection of 2000 short clips comprising 50 classes of various common sound events, and an abundant unified compilation of 250000 unlabeled auditory excerpts extracted from recordings available through the Freesound project. The paper also provides an evaluation of human accuracy in classifying environmental sounds and compares it to the performance of selected baseline classifiers using features derived from mel-frequency cepstral coefficients and zero-crossing rate.
The authors' abstract, as published at the source., 2015 · DOI ↗
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Field: Signal Processing
Signal ProcessingComputer Science