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ZENODO
Dataset . 2020
License: http://opensource.org/licenses/MIT
Data sources: ZENODO
ZENODO
Dataset . 2020
License: https://opensource.org/licenses/MIT
Data sources: Datacite
ZENODO
Dataset . 2020
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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Open-Unmix for Speech Enhancement (UMX SE)

Research datakeyboard_double_arrow_right Dataset 05 May 2020Publisher:Zenodo
Authors: Uhlich, Stefan; Mitsufuji, Yuki;

doi: 10.5281/zenodo.3786908 , 10.5281/zenodo.3786907

Open-Unmix for Speech Enhancement (UMX SE)

Abstract

Weights of Open-Unmix trained on the 28-speaker version of Voicebank+Demand (Sampling rate: 16kHz). The weights can be used with open-unmix-nnabla and open-unmix-pytorch.

Related Organizations
Keywords

NNabla, Source Separation, PyTorch, Speech Enhancement

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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
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89
95