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ZENODO
Software . 2020
License: https://creativecommons.org/licenses/by-sa/3.0/legalcode
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tmirzaev-dotcom/ConvTasNet_Libri3Mix_sepnoisy

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 09 Sep 2020Publisher:Zenodo
Authors: TakhirMirzaev;

doi: 10.5281/zenodo.4020529 , 10.5281/zenodo.4020528

tmirzaev-dotcom/ConvTasNet_Libri3Mix_sepnoisy

Abstract

Description: This model was trained by TakhirMirzaev using the librimix/ConvTasNet recipe in Asteroid. It was trained on the sep_noisy task of the Libri3Mix dataset. Training config:data: n_src: 3sample_rate: 8000segment: 3task: sep_noisytrain_dir: data/wav8k/min/train-360valid_dir: data/wav8k/min/devfilterbank: kernel_size: 16n_filters: 512stride: 8main_args: exp_dir: exp/train_convtasnet_my_taghelp: Nonemasknet: bn_chan: 128hid_chan: 512mask_act: relun_blocks: 8n_repeats: 3n_src: 3skip_chan: 128optim: lr: 0.001optimizer: adamweight_decay: 0.0positional arguments: training: batch_size: 4early_stop: Trueepochs: 200half_lr: Truenum_workers: 4 Results:si_sdr: 6.824750632456865 si_sdr_imp: 11.234803761803752 sdr: 7.715799858488098 sdr_imp: 11.778681386239114 sir: 16.442141130818637 sir_imp: 19.527535070051055 sar: 8.757864265661263 sar_imp: -0.15657258049670303 stoi: 0.7854554136619554 stoi_imp: 0.22267957718163015 License notice:This work "ConvTasNet_Libri3Mix_sepnoisy" is a derivative of LibriSpeech ASR corpus by Vassil Panayotov, used under CC BY 4.0; of The WSJ0 Hipster Ambient Mixtures dataset by Whisper.ai, used under CC BY-NC 4.0 (Research only). "ConvTasNet_Libri3Mix_sepnoisy" is licensed under Attribution-ShareAlike 3.0 Unported by TakhirMirzaev.

Keywords

ConvTasNet, sep_noisy, Asteroid, Libri3Mix, audio source separation, pretrained model

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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.
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This indicator 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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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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