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Main Authors: Sainburg, Tim, Zorea, Asaf
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.17851
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author Sainburg, Tim
Zorea, Asaf
author_facet Sainburg, Tim
Zorea, Asaf
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2412_17851
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Noisereduce: Domain General Noise Reduction for Time Series Signals
Sainburg, Tim
Zorea, Asaf
Signal Processing
Sound
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.
title Noisereduce: Domain General Noise Reduction for Time Series Signals
topic Signal Processing
Sound
url https://arxiv.org/abs/2412.17851