Update README.md

README.md

@@ -34,6 +34,8 @@ Please notice that we encourage you to read our tutorials and learn more about
 
 ### Perform Text-to-Speech (TTS)
 
+The following is an example of converting text-to-speech with the speaker voice characteristics extracted from reference speech.
+
 ```
 import torchaudio
 from speechbrain.pretrained import MSTacotron2
@@ -57,6 +59,31 @@ waveforms = hifi_gan.decode_batch(mel_outputs)
 torchaudio.save("synthesized_sample.wav", waveforms.squeeze(1).cpu(), 22050)
 ```
 
+If you want to generate a random voice, you can use the following:
+
+```
+import torchaudio
+from speechbrain.pretrained import MSTacotron2
+from speechbrain.pretrained import HIFIGAN
+
+# Intialize TTS (mstacotron2) and Vocoder (HiFIGAN)
+ms_tacotron2 = MSTacotron2.from_hparams(source="speechbrain/tts-mstacotron2-libritts", savedir="tmpdir_tts")
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-libritts-22050Hz", savedir="tmpdir_vocoder")
+
+# Required input
+INPUT_TEXT = "Mary had a little lamb"
+
+# Running the Zero-Shot Multi-Speaker Tacotron2 model to generate mel-spectrogram
+mel_outputs, mel_lengths, alignments = ms_tacotron2.generate_random_voice(INPUT_TEXT)
+
+# Running Vocoder (spectrogram-to-waveform)
+waveforms = hifi_gan.decode_batch(mel_outputs)
+
+# Save the waverform
+torchaudio.save("synthesized_sample.wav", waveforms.squeeze(1).cpu(), 22050)
+```
+
+
 If you want to generate multiple sentences in one-shot, you can do it this way:
 Note: The model internally reorders the input texts in the decreasing order of their lengths.