Spaces:
Running
on
Zero
Running
on
Zero
import spaces | |
import gradio as gr | |
import torch | |
from transformers.models.speecht5.number_normalizer import EnglishNumberNormalizer | |
from string import punctuation | |
import re | |
from parler_tts import ParlerTTSForConditionalGeneration | |
from transformers import AutoTokenizer, AutoFeatureExtractor, set_seed | |
device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
repo_id = "PHBJT/french_parler_tts_mini_v0.1" | |
model = ParlerTTSForConditionalGeneration.from_pretrained(repo_id).to(device) | |
tokenizer = AutoTokenizer.from_pretrained(repo_id) | |
feature_extractor = AutoFeatureExtractor.from_pretrained(repo_id) | |
SAMPLE_RATE = feature_extractor.sampling_rate | |
SEED = 42 | |
default_text = "La voix humaine est un instrument de musique au-dessus de tous les autres." | |
default_description = "A male voice speaks slowly with a very noisy background, displaying a touch of expressiveness and animation. The sound is very distant, adding an air of intrigue." | |
examples = [ | |
[ | |
"La voix humaine est un instrument de musique au-dessus de tous les autres.", | |
"A male voice speaks slowly with a very noisy background, displaying a touch of expressiveness and animation. The sound is very distant, adding an air of intrigue.", | |
None, | |
], | |
[ | |
"Tout ce qu'un homme est capable d'imaginer, d'autres hommes seront capables de le réaliser.", | |
"A male voice delivers a slightly expressive and animated speech with a moderate speed. The recording features a low-pitch voice, creating a close-sounding audio experience.", | |
None, | |
], | |
[ | |
"La machine elle-même, si perfectionnée qu'on la suppose, n'est qu'un outil.", | |
"A male voice provides a monotone yet slightly fast delivery, with a very close recording that almost has no background noise.", | |
None, | |
], | |
[ | |
"Le progrès fait naître plus de besoins qu'il n'en satisfait.", | |
"A female voice, in a very poor recording quality, delivers slightly expressive and animated words with a fast pace. There's a high level of background noise and a very distant-sounding reverberation. The voice is slightly higher pitched than average.", | |
None, | |
], | |
] | |
number_normalizer = EnglishNumberNormalizer() | |
def preprocess(text): | |
text = number_normalizer(text).strip() | |
text = text.replace("-", " ") | |
if text[-1] not in punctuation: | |
text = f"{text}." | |
abbreviations_pattern = r'\b[A-Z][A-Z\.]+\b' | |
def separate_abb(chunk): | |
chunk = chunk.replace(".","") | |
print(chunk) | |
return " ".join(chunk) | |
abbreviations = re.findall(abbreviations_pattern, text) | |
for abv in abbreviations: | |
if abv in text: | |
text = text.replace(abv, separate_abb(abv)) | |
return text | |
def gen_tts(text, description): | |
inputs = tokenizer(description.strip(), return_tensors="pt").to(device) | |
prompt = tokenizer(preprocess(text), return_tensors="pt").to(device) | |
set_seed(SEED) | |
generation = model.generate( | |
input_ids=inputs.input_ids, prompt_input_ids=prompt.input_ids, attention_mask=inputs.attention_mask, prompt_attention_mask=prompt.attention_mask, do_sample=True, temperature=1.0 | |
) | |
audio_arr = generation.cpu().numpy().squeeze() | |
return SAMPLE_RATE, audio_arr | |
css = """ | |
#share-btn-container { | |
display: flex; | |
padding-left: 0.5rem !important; | |
padding-right: 0.5rem !important; | |
background-color: #000000; | |
justify-content: center; | |
align-items: center; | |
border-radius: 9999px !important; | |
width: 13rem; | |
margin-top: 10px; | |
margin-left: auto; | |
flex: unset !important; | |
} | |
#share-btn { | |
all: initial; | |
color: #ffffff; | |
font-weight: 600; | |
cursor: pointer; | |
font-family: 'IBM Plex Sans', sans-serif; | |
margin-left: 0.5rem !important; | |
padding-top: 0.25rem !important; | |
padding-bottom: 0.25rem !important; | |
right:0; | |
} | |
#share-btn * { | |
all: unset !important; | |
} | |
#share-btn-container div:nth-child(-n+2){ | |
width: auto !important; | |
min-height: 0px !important; | |
} | |
#share-btn-container .wrap { | |
display: none !important; | |
} | |
""" | |
with gr.Blocks(css=css) as block: | |
gr.HTML( | |
""" | |
<div style="text-align: center; max-width: 700px; margin: 0 auto;"> | |
<div | |
style=" | |
display: inline-flex; align-items: center; gap: 0.8rem; font-size: 1.75rem; | |
" | |
> | |
<h1 style="font-weight: 900; margin-bottom: 7px; line-height: normal;"> | |
French Parler-TTS 🗣️ | |
</h1> | |
</div> | |
</div> | |
""" | |
) | |
gr.HTML( | |
f""" | |
<p><a href="https://github.com/huggingface/parler-tts">Parler-TTS</a> is a training and inference library for | |
high-fidelity text-to-speech (TTS) models.</p> | |
<p>The model demonstrated here, French Parler-TTS <a href="https://huggingface.co/PHBJT/french_parler_tts_mini_v0.1">Mini v0.1 French</a>, | |
has been fine-tuned on a French dataset. It generates high-quality speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation). | |
Due to limitations on the dataset, this model might underperform for female voices (we recommend using male voices only).</p> | |
<p>By default, Parler-TTS generates 🎲 random male voice characteristics. To ensure 🎯 <b>speaker consistency</b> across generations, try to use consistent descriptions in your prompts.</p> | |
<p><b>Note:</b> do NOT specify the nationnality of the speaker it will cause inconsistent audio generation (do: "a male speaker", don't: "a french male speaker") </p> | |
<p><b>Important note:</b> this model does NOT work in english, it will generate incoherent audios. But you can still use the original Parler TTS model for that. </p> | |
""" | |
) | |
with gr.Row(): | |
with gr.Column(): | |
input_text = gr.Textbox(label="Input Text", lines=2, value=default_text, elem_id="input_text") | |
description = gr.Textbox(label="Description", lines=2, value=default_description, elem_id="input_description") | |
run_button = gr.Button("Generate Audio", variant="primary") | |
with gr.Column(): | |
audio_out = gr.Audio(label="Parler-TTS generation", type="numpy", elem_id="audio_out", autoplay = True) | |
inputs = [input_text, description] | |
outputs = [audio_out] | |
run_button.click(fn=gen_tts, inputs=inputs, outputs=outputs, queue=True) | |
gr.Examples(examples=examples, fn=gen_tts, inputs=inputs, outputs=outputs, cache_examples=True) | |
gr.HTML( | |
""" | |
<p>Tips for ensuring good generation: | |
<ul> | |
<li>Include the term "very clear audio" to generate the highest quality audio, and "very noisy audio" for high levels of background noise</li> | |
<li>Punctuation can be used to control the prosody of the generations, e.g. use commas to add small breaks in speech</li> | |
<li>The remaining speech features (gender, speaking rate, pitch and reverberation) can be controlled directly through the prompt</li> | |
</ul> | |
</p> | |
""" | |
) | |
block.queue() | |
block.launch(share=True) |