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ZENODO
Software . 2020
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2020
Data sources: Datacite
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ZENODO
Software . 2020
Data sources: ZENODO
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Cosentino/ConvTasNet_LibriMix_sep_clean

Authors: Cosentino Joris;

Cosentino/ConvTasNet_LibriMix_sep_clean

Abstract

Description: This model was trained by Joris Cosentino using the librimix recipe in Asteroid. It was trained on the sep_clean task of the LibriMix dataset. Training config: data: n_src: 2 sample_rate: 8000 segment: 3 task: sep_clean train_dir: data/wav8k/min/train-360 valid_dir: data/wav8k/min/dev filterbank: kernel_size: 16 n_filters: 512 stride: 8 masknet: bn_chan: 128 hid_chan: 512 mask_act: relu n_blocks: 8 n_repeats: 3 skip_chan: 128 optim: lr: 0.001 optimizer: adam weight_decay: 0.0 positional arguments: training: batch_size: 24 early_stop: True epochs: 200 half_lr: True num_workers: 2 Results: si_sdr: 14.764543634468069 si_sdr_imp: 14.764029375607246 sdr: 15.29337970745095 sdr_imp: 15.114146605113111 sir: 24.092904661115366 sir_imp: 23.913669683141528 sar: 16.06055906916849 sar_imp: -51.980784441287454 stoi: 0.9311142440593033 stoi_imp: 0.21817376142710482 License notice: This work "ConvTasNet_Librisep_cleanMix_sepclean" is a derivative of LibriSpeech ASR corpus by Vassil Panayotov, used under CC BY 4.0. "ConvTasNet_Librisep_cleanMix_sepclean" is licensed under Attribution-ShareAlike 3.0 Unported by Cosentino Joris.

Keywords

ConvTasNet, Asteroid, audio source separation, sep_clean, pretrained model, Librisep_cleanMix

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selected citations
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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).
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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.
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