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Vctk Dns2020 Bsrnn Xtiny Noncausal

This model was trained by wyz based on the universalsev1 recipe in espnet. More information can be found at

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2.18 MB
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vRevision b6f990e
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Sep 18, 2026
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Hugging Face

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This model was trained by wyz based on the universalsev1 recipe in espnet. More information can be found at

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Hugging FacePrimaryVersion b6f990e444508b11fb6971b324ac5ce15d94124b
huggingface.co/wyz/vctk_dns2020_bsrnn_xtiny_noncausal/tree/b6f990e444508b11fb6971b324ac5ce15d94124b

Verified Sep 18

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exp_vctk_dns20/enh_train_enh_bsrnn_xtiny_noncausal_raw/97epoch.pth

pth · 2.18 MB · SHA-256 f89dac14324e…f445 · Hugging Face

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--- tags: - espnet - audio - audio-to-audio language: en datasets: - VCTK_DEMAND - DNS2020 license: cc-by-4.0 --- ## ESPnet2 ENH model ### `wyz/vctk_dns2020_bsrnn_xtiny_noncausal` This model was trained by wyz based on the universal_se_v1 recipe in [espnet](https://github.com/espnet/espnet/). More information can be found at https://github.com/Emrys365/se-scaling. ### Demo: How to use in ESPnet2 Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) if you haven't done that already. To use the model in the Python interface, you could use the following code: ```python import soundfile as sf from espnet2.bin.enh_inference import SeparateSpeech # For model downloading + loading model = SeparateSpeech.from_pretrained( model_tag="wyz/vctk_dns2020_bsrnn_xtiny_noncausal", normalize_output_wav=True, device="cuda", ) # For loading a downloaded model # model = SeparateSpeech( # train_config="exp_vctk_dns20/enh_train_enh_bsrnn_xtiny_noncausal_raw/config.yaml", # model_file="exp_vctk_dns20/enh_train_enh_bsrnn_xtiny_noncausal_raw/xxxx.pth", # normalize_output_wav=True, # device="cuda", # ) audio, fs = sf.read("/path/to/noisy/utt1.flac") enhanced = model(audio[None, :], fs=fs)[0] ``` <!-- Generated by ./scripts/utils/show_enh_score.sh --> # RESULTS ## Environments - date: `Wed Feb 28 00:03:12 EST 2024` - python version: `3.8.16 (default, Mar 2 2023, 03:21:46) [GCC 11.2.0]` - espnet version: `espnet 202304` - pytorch version: `pytorch 2.0.1+cu118` - Git hash: `443028662106472c60fe8bd892cb277e5b488651` - Commit date: `Thu May 11 03:32:59 2023 +0000` ## enhanced_test_16k |dataset|PESQ_WB|STOI|SAR|SDR|SIR|SI_SNR|OVRL|SIG|BAK|P808_MOS| |---|---|---|---|---|---|---|---|---|---|---| |chime4_et05_real_isolated_6ch_track|1.14|51.77|-3.09|-3.09|0.00|-31.08|2.68|3.01|3.74|3.54| |chime4_et05_simu_isolated_6ch_track|1.38|79.75|7.40|7.40|0.00|1.78|2.61|2.90|3.85|3.18| |dns20_tt_synthetic_no_reverb|2.89|96.71|17.93|17.93|0.00|17.89|3.26|3.52|4.06|4.01| |reverb_et_real_8ch_multich|1.36|78.42|9.46|9.46|0.00|5.51|2.81|3.13|3.88|3.53| |reverb_et_simu_8ch_multich|1.59|82.97|8.98|8.98|0.00|-10.79|2.83|3.27|3.65|3.65| |whamr_tt_mix_single_reverb_max_16k|1.40|81.87|6.87|6.87|0.00|1.80|2.76|3.09|3.82|3.57| ## enhanced_test_48k |dataset|STOI|SAR|SDR|SIR|SI_SNR|OVRL|SIG|BAK|P808_MOS| |---|---|---|---|---|---|---|---|---|---| |vctk_nois...

Source context: 1 downloads · 0 likes · Pipeline audio-to-audio · Library espnet · Repo wyz/vctk_dns2020_bsrnn_xtiny_noncausal