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---
language:
- lg
tags:
- text-to-speech
- TTS
- speech-synthesis
- Tacotron2
- speechbrain
license: apache-2.0
datasets:
- SALT-TTS
metrics:
- mos
---
# Sunbird AI Text-to-Speech (TTS) model trained on Luganda text
### Text-to-Speech (TTS) with Tacotron2 trained on Male Commonvoice Recordings
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)
```
import torchaudio
from speechbrain.pretrained import Tacotron2
from speechbrain.pretrained import HIFIGAN
# Intialize TTS (tacotron2) and Vocoder (HiFIGAN)
tacotron2 = Tacotron2.from_hparams(source="sunbird/sunbird-lug-tts-commonvoice-male", 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("Mbagaliza Christmass Enungi Nomwaka Omugya Gubaberere Gwamirembe")
# 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 = [
"Nsanyuse okukulaba",
"Erinnya lyo ggwe ani?",
"Mbagaliza Christmass Enungi Nomwaka Omugya Gubaberere Gwamirembe"
]
mel_outputs, mel_lengths, alignments = tacotron2.encode_batch(items)
```
### Inference on GPU
To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method. |