Update README.md

README.md

@@ -4,8 +4,6 @@ tags:
 - audio
 - audio-to-audio
 language: en
-datasets:
-- universal_se
 license: cc-by-4.0
 ---
 
@@ -13,18 +11,35 @@ license: cc-by-4.0
 
 ### `wyz/vctk_bsrnn_xtiny_causal`
 
-This model was trained by Emrys365 using universal_se recipe in [espnet](https://github.com/espnet/espnet/).
+This model was trained by Emrys365 based on the universal_se_v1 recipe in [espnet](https://github.com/espnet/espnet/).
 
 ### 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.
 
-```bash
-cd espnet
-pip install -e .
-cd egs2/universal_se/enh1
-./run.sh --skip_data_prep false --skip_train true --download_model wyz/vctk_bsrnn_xtiny_causal
+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_xtiny_causal",
+    normalize_output_wav=True,
+    device="cuda",
+)
+# For loading a downloaded model
+# model = SeparateSpeech(
+#     train_config="exp_vctk/xxx/config.yaml",
+#     model_file="exp_vctk/xx/xxxx.pth",
+#     normalize_output_wav=True,
+#     device="cuda",
+# )
+
+audio, fs = sf.read("/path/to/noisy/utt1.flac")
+enhanced = model(audio[None, :], fs=fs)[0]
 ```
 
 
@@ -323,4 +338,4 @@ or arXiv:
   archivePrefix={arXiv},
   primaryClass={cs.CL}
 }
-```
+```