Vctk Bsrnn Small Noncausal
This model was trained by wyz based on the universalsev1 recipe in espnet. More information can be found at
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- Kind
- Other
- File size
- 18.5 MB
- Version
- vRevision eae5576
- Updated
- Sep 19, 2026
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- 5
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- Audio
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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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1 source
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1 sourceVerified Sep 19
Model artifacts
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Model artifacts
1 artifactexp_vctk/enh_train_enh_bsrnn_small_noncausal_raw/58epoch.pth
pth · 18.5 MB · SHA-256 c6d4edcb2e2b…fd8f · Hugging Face
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Source excerpts
2 excerpts--- tags: - espnet - audio - audio-to-audio language: en datasets: - VCTK_DEMAND license: cc-by-4.0 --- ## ESPnet2 ENH model ### `wyz/vctk_bsrnn_small_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_small_noncausal", normalize_output_wav=True, device="cuda", ) # For loading a downloaded model # model = SeparateSpeech( # train_config="exp_vctk/enh_train_enh_bsrnn_small_noncausal_raw/config.yaml", # model_file="exp_vctk/enh_train_enh_bsrnn_small_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 10:43:40 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|48.47|-3.59|-3.59|0.00|-31.33|2.72|3.05|3.70|3.40| |chime4_et05_simu_isolated_6ch_track|1.20|69.10|5.17|5.17|0.00|-0.97|2.54|2.84|3.72|3.03| |dns20_tt_synthetic_no_reverb|2.20|93.38|13.69|13.69|0.00|12.74|3.21|3.53|3.95|3.85| |reverb_et_real_8ch_multich|1.06|39.76|-0.78|-0.78|0.00|-5.26|2.05|2.37|3.35|2.73| |reverb_et_simu_8ch_multich|1.47|74.58|7.08|7.08|0.00|-12.38|2.80|3.13|3.78|3.45| |whamr_tt_mix_single_reverb_max_16k|1.27|73.26|4.50|4.50|0.00|0.23|2.59|2.90|3.75|3.31| ## enhanced_test_48k |dataset|STOI|SAR|SDR|SIR|SI_SNR|OVRL|SIG|BAK|P808_MOS| |---|---|---|---|---|---|---|---|---|---| |vctk_noisy_tt_2spk|95.16|20.27|20.27|0.00|...
Source context: 5 downloads · 0 likes · Pipeline audio-to-audio · Library espnet · Repo wyz/vctk_bsrnn_small_noncausal
