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Vctk Bsrnn Medium Noncausal

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

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64.7 MB
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vRevision 8f95f0c
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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 8f95f0c39accdb1b638585e66e6f00f06c89055b
huggingface.co/wyz/vctk_bsrnn_medium_noncausal/tree/8f95f0c39accdb1b638585e66e6f00f06c89055b

Verified Sep 18

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exp_vctk/enh_train_enh_bsrnn_medium_noncausal_raw/58epoch.pth

pth · 64.7 MB · SHA-256 a607e0a6faa7…5f0b · Hugging Face

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--- tags: - espnet - audio - audio-to-audio language: en datasets: - VCTK_DEMAND license: cc-by-4.0 --- ## ESPnet2 ENH model ### `wyz/vctk_bsrnn_medium_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_bsrnn_medium_noncausal", normalize_output_wav=True, device="cuda", ) # For loading a downloaded model # model = SeparateSpeech( # train_config="exp_vctk/enh_train_enh_bsrnn_medium_noncausal_raw/config.yaml", # model_file="exp_vctk/enh_train_enh_bsrnn_medium_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 01:40:25 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|1.11|48.88|-3.44|-3.44|0.00|-31.29|2.78|3.09|3.79|3.47| |chime4_et05_simu_isolated_6ch_track|1.22|69.37|5.61|5.61|0.00|-0.58|2.60|2.89|3.80|3.13| |dns20_tt_synthetic_no_reverb|2.34|93.88|14.32|14.32|0.00|13.42|3.27|3.56|4.02|3.91| |reverb_et_real_8ch_multich|1.06|37.83|0.59|0.59|0.00|-4.19|2.19|2.51|3.50|2.88| |reverb_et_simu_8ch_multich|1.55|77.68|7.89|7.89|0.00|-11.68|2.91|3.24|3.84|3.58| |whamr_tt_mix_single_reverb_max_16k|1.28|73.13|4.95|4.95|0.00|0.52|2.66|2.95|3.83|3.38| ## enhanced_test_48k |dataset|STOI|SAR|SDR|SIR|SI_SNR|OVRL|SIG|BAK|P808_MOS| |---|---|---|---|---|---|---|---|---|---| |vctk_noisy_tt_2spk|95.08|20.39|20.39|0.0...

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