ArticleScientific data2025
Environmental Noise Dataset for Sound Event Classification and Detection.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Environmental Noise Dataset for Sound Event Classification and Detection.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Sound Event Classification (SEC) and Sound Event Detection (SED) are gaining momentum across various domains. With the rise of machine learning, identifying specific sound sources amid background noise in outdoor environments has become a major focus. Recognizable sound types are many and vary depending on context, ranging from vehicles, trains, and aircraft to human and animal activity. This work introduces two open-access datasets, DataSEC and DataSED, created to address gaps identified in the existing dataset literature. Together, they provide over 35 hours of authentic, non-synthesized.wav audio, collected from sound level meter measurements and online repositories. DataSEC consists of 4292 audio samples, with each sample representing a single event that has been classified into one of 22 defined sound classes and 28 subclasses. DataSED comprises 712 real-world recordings containing multiple events, accompanied by over 4000 labels provided in .csv format. These datasets extend across a range of urban to rural environments and have been designed to support research in real-world sound event classification and automated analysis of environmental noise.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.