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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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3 results for “DCASE2019”

A hybrid parametric-deep learning approach for sound event localization and detectioncs.SD

Reduces sound event localization error by 2.6x with hybrid parametric-deep learning.

problem Sound event localization and detection accuracy.

method Hybrid approach combining parametric spatial audio analysis and deep learning.

result Reduction of localization error by 2.6x compared to baseline.

sound event localization deep learning parametric analysis DCASE2019

2019-08-27abs ↗pdf ↗

Audio tagging with noisy labels and minimal supervisioncs.SD

This paper introduces Task 2 of the DCASE2019 Challenge, titled "Audio tagging with noisy labels and minimal supervision". This task was hosted on the Kaggle platform as "Freesound Audio Tagging 2019". The task evaluates systems for multi-label audio tagging using a large set of noisy-labeled data, and a much smaller s…

2019-06-07abs ↗pdf ↗

Sound source detection, localization and classification using consecutive ensemble of CRNN modelseess.AS

The paper presents a method for sound event localization and detection using CRNN models.

problem Sound event localization and detection in complex environments.

method Consecutive ensemble of CRNN models for estimating event onset, offset, direction of arrival, and classification.

result The proposed method outperforms other participants in the DCASE2019 task3.

sound event localization sound event detection CRNN models ensemble learning direction of arrival

2019-08-02abs ↗pdf ↗