Create README.md

README.md

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+---
+datasets:
+- mozilla-foundation/common_voice_17_0
+language:
+- lg
+base_model:
+- speechbrain/tts-tacotron2-ljspeech
+pipeline_tag: text-to-speech
+metrics:
+- mos
+---
+
+<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
+<br/><br/>
+
+
+# Text-to-Speech (TTS) with Tacotron2 trained on Luganda CommonVoice
+
+This repository provides all the necessary tools for Text-to-Speech (TTS)  with SpeechBrain.
+
+The pre-trained model takes in input a short text and produces a spectrogram in output. One can get the final waveform by applying a vocoder (e.g., HiFIGAN) on top of the generated spectrogram.
+
+
+## Install SpeechBrain
+
+```
+pip install speechbrain
+```
+
+Please notice that we encourage you to read our tutorials and learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+### Perform Text-to-Speech (TTS)
+
+```python
+import torchaudio
+from speechbrain.inference.TTS import Tacotron2
+from speechbrain.inference.vocoders import HIFIGAN
+
+# Intialize TTS (tacotron2) and Vocoder (HiFIGAN)
+tacotron2 = Tacotron2.from_hparams(source="sulaimank/tacotron2-cv-females", savedir="tmpdir_tts")
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmpdir_vocoder")
+
+# Running the TTS
+mel_output, mel_length, alignment = tacotron2.encode_text("Mary had a little lamb")
+
+# Running Vocoder (spectrogram-to-waveform)
+waveforms = hifi_gan.decode_batch(mel_output)
+
+# Save the waverform
+torchaudio.save('example_TTS.wav',waveforms.squeeze(1), 22050)
+```
+
+If you want to generate multiple sentences in one-shot, you can do in this way:
+
+```
+from speechbrain.pretrained import Tacotron2
+tacotron2 = Tacotron2.from_hparams(source="speechbrain/TTS_Tacotron2", savedir="tmpdir")
+items = [
+       "A quick brown fox jumped over the lazy dog",
+       "How much wood would a woodchuck chuck?",
+       "Never odd or even"
+     ]
+mel_outputs, mel_lengths, alignments = tacotron2.encode_batch(items)
+
+### Limitations
+The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
+
+```