{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Text-to-Speech web inference using Gradio"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"STT Mel synthesis + Vocoder"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"This tutorial is available as an IPython notebook at [malaya-speech/example/tts-gradio](https://github.com/huseinzol05/malaya-speech/tree/master/example/tts-gradio).\n",
" \n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"This module is not language independent, so it not save to use on different languages. Pretrained models trained on hyperlocal languages.\n",
" \n",
"
"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import malaya_speech\n",
"import numpy as np\n",
"from malaya_speech import Pipeline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For this example, I am going to use GlowTTS. Feel free to use any TTS model."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List available GlowTTS"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Size (MB) | \n",
" Quantized Size (MB) | \n",
" Understand punctuation | \n",
" Is lowercase | \n",
"
\n",
" \n",
" \n",
" \n",
" | male | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" True | \n",
"
\n",
" \n",
" | female | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" True | \n",
"
\n",
" \n",
" | haqkiem | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" True | \n",
"
\n",
" \n",
" | female-singlish | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" True | \n",
"
\n",
" \n",
" | yasmin | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" False | \n",
"
\n",
" \n",
" | osman | \n",
" 119 | \n",
" 27.6 | \n",
" True | \n",
" False | \n",
"
\n",
" \n",
" | multispeaker | \n",
" 404 | \n",
" 79.9 | \n",
" True | \n",
" True | \n",
"
\n",
" \n",
"
\n",
"