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---
tags:
- tensorflowtts
- audio
- text-to-speech
- text-to-mel
language: vi
license: mit
datasets:
- InfoRe
---
# How to use
## Install TensorFlowTTS
```
pip install TensorFlowTTS
```
### Converting your Text to Mel Spectrogram
```python
import numpy as np
import soundfile as sf
import yaml
import IPython.display as ipd
import tensorflow as tf
from tensorflow_tts.inference import AutoProcessor
from tensorflow_tts.inference import TFAutoModel
from tensorflow_tts.inference import AutoConfig
processor = AutoProcessor.from_pretrained(pretrained_path="./processor.json")
config = AutoConfig.from_pretrained("./config.yml")
fastspeech2 = TFAutoModel.from_pretrained(
config=config,
pretrained_path="./model.h5"
)
text = "xin chào đây là một ví dụ về chuyển đổi văn bản thành giọng nói"
input_ids = processor.text_to_sequence(text)
mel_before, mel_after, duration_outputs, _, _ = fastspeech2.inference(
input_ids=tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
speaker_ids=tf.convert_to_tensor([0], dtype=tf.int32),
speed_ratios=tf.convert_to_tensor([1.0], dtype=tf.float32),
f0_ratios =tf.convert_to_tensor([1.0], dtype=tf.float32),
energy_ratios =tf.convert_to_tensor([1.0], dtype=tf.float32),
)
```
#### Bonus: Convert Mel Spectrogram to Speech
```python
mb_melgan = TFAutoModel.from_pretrained("tensorspeech/tts-mb_melgan-ljspeech-en")
audio_before = mb_melgan.inference(mel_before)[0, :, 0]
audio_after = mb_melgan.inference(mel_after)[0, :, 0]
sf.write("audio_before.wav", audio_before, 22050, "PCM_16")
sf.write("audio_after.wav", audio_after, 22050, "PCM_16")
ipd.Audio('audio_after.wav')
``` |