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import gradio as gr
import tempfile
from TTS.api import TTS
from huggingface_hub import hf_hub_download
import torch
CUDA = torch.cuda.is_available()
REPO_ID = "ayymen/Coqui-TTS-Vits-Multispeaker"
VOICE_CONVERSION_MODELS = {
'freevc24': 'voice_conversion_models/multilingual/vctk/freevc24',
'openvoice_v1': 'voice_conversion_models/multilingual/multi-dataset/openvoice_v1',
'openvoice_v2': 'voice_conversion_models/multilingual/multi-dataset/openvoice_v2',
}
VARIANTS = {"Tachelhit": "shi", "Tarifit": "rif"}
SPEAKERS = ["yan", "sin", "idj"]
my_title = "ⴰⴹⵕⵉⵚ ⵙ ⵉⵎⵙⵍⵉ - Tamazight Text-to-Speech"
my_description = "This model is based on [VITS](https://github.com/jaywalnut310/vits), thanks to 🐸 [Coqui.ai](https://coqui.ai/)."
my_examples = [
["ⴰⵣⵓⵍ. ⵎⴰⵏⵣⴰⴽⵉⵏ?", "shi", "yan", True],
["ⵡⴰ ⵜⴰⵎⵖⴰⵔⵜ ⵎⴰ ⴷ ⵓⴽⴰⵏ ⵜⵙⴽⵔⵜ?", "shi", "sin", False],
["ⴳⵏ ⴰⴷ ⴰⴽ ⵉⵙⵙⴳⵏ ⵕⴱⴱⵉ ⵉⵜⵜⵓ ⴽ.", "shi", "yan", False],
["ⴰⵔⵔⴰⵡ ⵏ ⵍⵀⵎⵎ ⵢⵓⴽⵔ ⴰⵖ ⵉⵀⴷⵓⵎⵏ ⵏⵏⵖ!", "shi", "yan", False],
["ⴰⵣⵓⵍ. ⵎⴰⵎⵛ ⵜⴷⵊⵉⵜ?", "rif", "idj", True],
["ⴰⵇⵎⵎⵓⵎ ⵉⵇⵏⴻⵏ ⵓⵔ ⵜ ⵜⵜⵉⴷⴼⵏ ⵉⵣⴰⵏ.", "rif", "idj", False],
["ⵇⵇⵉⵎ ⵅ ⵜⴰⴷⴷⴰⵔⵜ ⵏⵏⵛ!", "rif", "idj", False],
["ⵜⴻⵜⵜⵏ ⴰⴳ ⵡⵓⵛⵛⵏ, ⵜⵜⵔⵓⵏ ⵅ ⵓⵎⴽⵙⴰ.", "rif", "idj", False]
]
my_inputs = [
gr.Textbox(lines=5, label="Input Text", placeholder="The only available characters are: ⴰⴱⴳⴷⴹⴻⴼⴽⵀⵃⵄⵅⵇⵉⵊⵍⵎⵏⵓⵔⵕⵖⵙⵚⵛⵜⵟⵡⵢⵣⵥⵯ !,.:?"),
gr.Dropdown(label="Variant", choices=list(VARIANTS.items()), value="shi"),
gr.Dropdown(label="Speaker", choices=SPEAKERS, value="yan"),
gr.Checkbox(label="Split Sentences (each sentence will be generated separately)", value=False),
gr.Audio(type="filepath", label="Speaker audio for voice cloning (optional)"),
gr.Dropdown(label="Voice Conversion Model", choices=list(VOICE_CONVERSION_MODELS.keys())),
]
my_outputs = gr.Audio(type="filepath", label="Output Audio", autoplay=True)
best_model_path = hf_hub_download(repo_id=REPO_ID, filename="checkpoint_390000.pth")
config_path = hf_hub_download(repo_id=REPO_ID, filename="config.json")
api = TTS(model_path=best_model_path, config_path=config_path).to("cuda" if CUDA else "cpu")
# pre-download voice conversion models
for model in VOICE_CONVERSION_MODELS.values():
api.load_vc_model_by_name(model, gpu=CUDA)
def tts(text: str, variant: str = "shi", speaker: str = "yan", split_sentences: bool = False, speaker_wav: str = None, voice_cv_model: str = 'freevc24'):
# replace oov characters
text = text.replace("\n", ". ")
text = text.replace("(", ",")
text = text.replace(")", ",")
text = text.replace('"', ",")
text = text.replace("'", ",")
text = text.replace(";", ",")
text = text.replace("-", " ")
with tempfile.NamedTemporaryFile(suffix = ".wav", delete = False) as fp:
if speaker_wav:
api.load_vc_model_by_name(VOICE_CONVERSION_MODELS[voice_cv_model], gpu=CUDA)
api.tts_with_vc_to_file(text, speaker_wav=speaker_wav, file_path=fp.name, split_sentences=split_sentences, speaker=speaker, language=variant)
else:
api.tts_to_file(text, file_path=fp.name, split_sentences=split_sentences, speaker=speaker, language=variant)
return fp.name
iface = gr.Interface(
fn=tts,
inputs=my_inputs,
outputs=my_outputs,
title=my_title,
description=my_description,
examples=my_examples,
cache_examples=True
)
iface.launch()
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