Vctk Dns2020 Whamr Conv Tasnet Small
This model was trained by wyz based on the universalsev1 recipe in espnet. More information can be found at
Model source
- Kind
- Other
- File size
- 11 B–4.39 MB
- Version
- vRevision 59dcca7
- Updated
- Sep 19, 2026
- Downloads
- 1
- Tasks
- Audio
- Source
- Hugging Face
Source excerpt
This model was trained by wyz based on the universalsev1 recipe in espnet. More information can be found at
Sources
1 source
Sources
1 sourceVerified Sep 19
Model artifacts
2 artifacts
Model artifacts
2 artifactsexp_vctk_dns20_whamr/enh_train_enh_conv_tasnet_small_raw/44epoch.pth
pth · 4.39 MB · SHA-256 c6941f087fee…0393 · Hugging Face
Downloadexp_vctk_dns20_whamr/enh_train_enh_conv_tasnet_small_raw/valid.loss.best.pth
pth · 11 B · Hugging Face
Source excerpts
2 excerpts
Source excerpts
2 excerpts--- tags: - espnet - audio - audio-to-audio language: en datasets: - VCTK_DEMAND - DNS2020 - WHAMR license: cc-by-4.0 --- ## ESPnet2 ENH model ### `wyz/vctk_dns2020_whamr_conv_tasnet_small` 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_whamr_conv_tasnet_small", normalize_output_wav=True, device="cuda", ) # For loading a downloaded model # model = SeparateSpeech( # train_config="exp_vctk_dns20_whamr/enh_train_enh_conv_tasnet_small_raw/config.yaml", # model_file="exp_vctk_dns20_whamr/enh_train_enh_conv_tasnet_small_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: `Thu Feb 29 00:21:34 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|1.21|53.13|-2.72|-2.72|0.00|-31.10|2.85|3.22|3.71|3.24| |chime4_et05_simu_isolated_6ch_track|1.41|82.10|7.96|7.96|0.00|1.39|2.80|3.12|3.84|3.04| |dns20_tt_synthetic_no_reverb|2.51|95.75|15.75|15.75|0.00|15.74|3.19|3.49|3.96|3.76| |reverb_et_real_8ch_multich|1.22|70.41|3.82|3.82|0.00|1.50|2.85|3.24|3.70|3.42| |reverb_et_simu_8ch_multich|1.64|87.62|9.39|9.39|0.00|-9.93|2.86|3.30|3.64|3.58| |whamr_tt_mix_single_reverb_max_16k|1.74|89.96|9.31|9.31|0.00|6.20|3.12|3.39|4.02|3.41| ## enhanced_test_48k |dataset|STOI|SAR|SDR|SIR|SI_SNR|OVRL|SIG|BAK|P808_MOS| |---|---|---|---|---|---|---|---|---|--...
Source context: 1 downloads · 0 likes · Pipeline audio-to-audio · Library espnet · Repo wyz/vctk_dns2020_whamr_conv_tasnet_small
