ArticleScientific reports2025
Domain general noise reduction for time series signals with Noisereduce.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Investigating the structure of the greylag goose vocal repertoire: what can unsupervised methods tell us?Scientific reports · 2026Article
- Encoding of speech modes and loudness in ventral precentral gyrus.Nature communications · 2026Article
- Novel Approach to Inter-Onset-Interval Ratio Uncovers Music-Like Rhythmic Patterns in Budgerigar (Melopsittacus undulatus) Warble Song.Annals of the New York Academy of Sciences · 2026Article
- A longitudinal multimodal big data infrastructure for precision poultry monitoring.Frontiers in big data · 2026Article
- Encoding of speech modes and loudness in ventral precentral gyrus.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
2 authors.
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Abstract
Extracting signals from noisy backgrounds is a fundamental problem in signal processing across a variety of domains. In this paper, we introduce Noisereduce, an algorithm for minimizing noise across a variety of domains, including speech, bioacoustics, neurophysiology, and seismology. Noisereduce uses spectral gating to estimate a frequency-domain mask that effectively separates signals from noise. It is fast, lightweight, requires no training data, and handles both stationary and non-stationary noise, making it both a versatile tool and a convenient baseline for comparison with domain-specific applications. We provide a detailed overview of Noisereduce and evaluate its performance on a variety of time-domain signals.
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