Update README.md

README.md

@@ -34,17 +34,37 @@ Please notice that we encourage you to read our tutorials and learn more about
 [SpeechBrain](https://speechbrain.github.io).
 
 
-### Transcribing your own audio files
+### Using the Vocoder
 
 ```python
 from speechbrain.pretrained import UnitHIFIGAN
 
-hifi_gan_unit = UnitHIFIGAN.from_hparams(source="speechbrain/hifigan-unit-hubert-l6-k100-ljspeech")
+hifi_gan_unit = UnitHIFIGAN.from_hparams(source="speechbrain/tts-hifigan-unit-hubert-l6-k100-ljspeech", savedir=tmpdir_vocoder)
 codes = torch.randint(0, 99, (100,))
 waveform = hifi_gan.decode_unit(codes)
 
 ```
 
+### Using the Vocoder with the S2UT
+```python
+import torchaudio
+from speechbrain.pretrained import EncoderDecoderS2UT
+from speechbrain.pretrained import UnitHIFIGAN
+
+# Intialize S2UT (Transformer) and Vocoder (HiFIGAN Unit)
+s2ut = EncoderDecoderS2UT.from_hparams(source="speechbrain/s2st-transformer-fr-en-hubert-l6-k100-cvss", savedir=tmpdir_s2ut)
+hifi_gan_unit = UnitHIFIGAN.from_hparams(source="speechbrain/tts-hifigan-unit-hubert-l6-k100-ljspeech", savedir=tmpdir_vocoder)
+
+# Running the S2UT model
+codes = s2ut.translate_file("speechbrain/s2st-transformer-fr-en-hubert-l6-k100-cvss/example-fr.wav")
+
+# Running Vocoder (units-to-waveform)
+waveforms = hifi_gan.decode_unit(codes)
+
+# Save the waverform
+torchaudio.save('example_TTS.wav',waveforms.squeeze(1), 16000)
+```
+
 ### Inference on GPU
 To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.