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on
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Running
on
Zero
import gradio as gr | |
import spaces | |
from styletts2 import tts | |
import re | |
import numpy as np | |
from scipy.io.wavfile import write | |
import nltk | |
nltk.download('punkt') | |
from nltk.tokenize import word_tokenize | |
import torch | |
import phonemizer # en-us | |
INTRO = """ | |
<style> | |
.TitleContainer { | |
background-color: #ffff; | |
margin-bottom: 0rem; | |
margin-left: auto; | |
margin-right: auto; | |
width: 40%; | |
height: 30%; | |
border-radius: 10rem; | |
border: 0.5vw solid #ff593e; | |
text-align: center; | |
display: flex; | |
justify-content: center; | |
transition: .6s; | |
} | |
.TitleContainer:hover { | |
transform: scale(1.05); | |
} | |
.VokanLogo { | |
margin: auto; | |
display: block; | |
} | |
</style> | |
<div class="TitleContainer"> | |
<img src="https://huggingface.co/spaces/ShoukanLabs/Vokan/resolve/main/Vokan.gif" class="VokanLogo"> | |
</div> | |
<p align="center", style="font-size: 1vw; font-weight: bold; color: #ff593e;">A StyleTTS2 fine-tune, designed for expressiveness.</p> | |
<hr> | |
""" | |
js_func = """ | |
function refresh() { | |
const url = new URL(window.location); | |
if (url.searchParams.get('__theme') !== 'light') { | |
url.searchParams.set('__theme', 'light'); | |
window.location.href = url.href; | |
} | |
} | |
""" | |
examples = [ | |
["./Examples/David Attenborough.wav", | |
"An understanding of the natural world is a source of not only great curiosity, but great fulfilment.", | |
1, 0.2, 0.5, 1, 200], | |
["./Examples/Linus Tech Tips.wav", | |
"sometimes I get so in the zone while building a computer it's like an out of body experience.", | |
1, 0.2, 0.8, 2, 200], | |
["./Examples/Melina.wav", | |
"If you intend to claim the Frenzied Flame, I ask that you cease. It is not to be meddled with. It is chaos, " | |
"devouring life and thought unending. However ruined this world has become, " | |
"however mired in torment and despair, life endures.", | |
0.95, 0.2, 0.5, 2, 200], | |
["./Examples/Patrick Bateman.wav", | |
"My Pain Is Constant And Sharp, And I Do Not Wish For A Better World For Anyone.", | |
1, 0.1, 0.3, 2, 200], | |
["./Examples/Furina.ogg", | |
"That's more like it! As expected, my dazzling side comes through in any situation.", | |
1, 0.2, 0.8, 2, 200] | |
] | |
theme = gr.themes.Soft( | |
primary_hue=gr.themes.Color(c100="#ffd7d1", c200="#ff593e", c300="#ff593e", c400="#ff593e", c50="#fff0f0", | |
c500="#ff593e", c600="#ea580c", c700="#c2410c", c800="#9a3412", c900="#7c2d12", | |
c950="#6c2e12"), | |
secondary_hue="orange", | |
radius_size=gr.themes.Size(lg="20px", md="8px", sm="6px", xl="30px", xs="4px", xxl="40px", xxs="2px"), | |
font=[gr.themes.GoogleFont('M PLUS Rounded 1c'), 'ui-sans-serif', 'system-ui', 'sans-serif'], | |
).set( | |
block_background_fill='*neutral_50' | |
) | |
# eventually swap to something else | |
global_phonemizer = phonemizer.backend.EspeakBackend(language='en-us', | |
preserve_punctuation=True, | |
with_stress=True, | |
language_switch="remove-flags", | |
tie=False) | |
def split_and_recombine_text(text, desired_length=200, max_length=300): | |
"""Split text it into chunks of a desired length trying to keep sentences intact.""" | |
# normalize text, remove redundant whitespace and convert non-ascii quotes to ascii | |
text = re.sub(r'\n\n+', '\n', text) | |
text = re.sub(r'\s+', ' ', text) | |
text = re.sub(r'[ββ]', '"', text) | |
rv = [] | |
in_quote = False | |
current = "" | |
split_pos = [] | |
pos = -1 | |
end_pos = len(text) - 1 | |
def seek(delta): | |
nonlocal pos, in_quote, current | |
is_neg = delta < 0 | |
for _ in range(abs(delta)): | |
if is_neg: | |
pos -= 1 | |
current = current[:-1] | |
else: | |
pos += 1 | |
current += text[pos] | |
if text[pos] == '"': | |
in_quote = not in_quote | |
return text[pos] | |
def peek(delta): | |
p = pos + delta | |
return text[p] if p < end_pos and p >= 0 else "" | |
def commit(): | |
nonlocal rv, current, split_pos | |
rv.append(current) | |
current = "" | |
split_pos = [] | |
while pos < end_pos: | |
c = seek(1) | |
# do we need to force a split? | |
if len(current) >= max_length: | |
if len(split_pos) > 0 and len(current) > (desired_length / 2): | |
# we have at least one sentence and we are over half the desired length, seek back to the last split | |
d = pos - split_pos[-1] | |
seek(-d) | |
else: | |
# no full sentences, seek back until we are not in the middle of a word and split there | |
while c not in '!?.\n ' and pos > 0 and len(current) > desired_length: | |
c = seek(-1) | |
commit() | |
# check for sentence boundaries | |
elif not in_quote and (c in '!?\n' or (c == '.' and peek(1) in '\n ')): | |
# seek forward if we have consecutive boundary markers but still within the max length | |
while pos < len(text) - 1 and len(current) < max_length and peek(1) in '!?.': | |
c = seek(1) | |
split_pos.append(pos) | |
if len(current) >= desired_length: | |
commit() | |
# treat end of quote as a boundary if its followed by a space or newline | |
elif in_quote and peek(1) == '"' and peek(2) in '\n ': | |
seek(2) | |
split_pos.append(pos) | |
rv.append(current) | |
# clean up, remove lines with only whitespace or punctuation | |
rv = [s.strip() for s in rv] | |
rv = [s for s in rv if len(s) > 0 and not re.match(r'^[\s\.,;:!?]*$', s)] | |
return rv | |
def text_to_phonemes(text): | |
text = text.strip() | |
print("Text before phonemization: ", text) | |
ps = global_phonemizer.phonemize([text]) | |
print("Text after phonemization: ", ps) | |
ps = word_tokenize(ps[0]) | |
ps = ' '.join(ps) | |
print("Final text after tokenization: ", ps) | |
return ps | |
def generate(audio_path, ins, speed, alpha, beta, embedding, steps=200): | |
ref_s = other_tts.compute_style(audio_path) | |
print(ref_s.size()) | |
s_prev = None | |
texts = split_and_recombine_text(ins) | |
audio = np.array([]) | |
for i in texts: | |
i = text_to_phonemes(i) | |
synthaud, s_prev = other_tts.long_inference_segment(i, diffusion_steps=steps, | |
alpha=alpha, beta=beta, is_phonemes=True, | |
embedding_scale=embedding, prev_s=s_prev, ref_s=ref_s, | |
speed=speed, t=0.8) | |
n_trim = int(len(synthaud) * 0.009) | |
synthaud[:n_trim] = 0 | |
synthaud[-n_trim:] = 0 | |
audio = np.concatenate((audio, synthaud)) | |
scaled = np.int16(audio / np.max(np.abs(audio)) * 32767) | |
return 24000, scaled | |
other_tts = tts.StyleTTS2(model_checkpoint_path='./epoch_2nd_00012.pth', config_path="models/config_ft.yml") | |
if torch.cuda.is_available(): | |
other_tts.devuce = "cuda" | |
else: | |
other_tts.device = "cpu" | |
with gr.Blocks(theme=theme, js=js_func) as clone: | |
gr.HTML(INTRO) | |
with gr.Row(): | |
with gr.Column(scale=1): | |
inp = gr.Textbox(label="Text", info="What do you want Vokan to say? | Longform generation may produce artifacts in between sentences", interactive=True) | |
voice = gr.Audio(label="Voice", interactive=True, type='filepath', max_length=1000, | |
waveform_options={'waveform_progress_color': '#FF593E'}) | |
steps = gr.Slider(minimum=3, maximum=500, value=20, step=1, label="Diffusion Steps", | |
info="Higher produces better results typically", interactive=True) | |
embscale = gr.Slider(minimum=0.1, maximum=5, value=2, step=0.1, label="Embedding Scale", | |
info="Defaults to 2 | high scales may produce unexpected results | Higher scales produce more emotion guided reults", interactive=True) | |
alpha = gr.Slider(minimum=0, maximum=1, value=0.3, step=0.1, label="Alpha", info="Defaults to 0.3 | Lower = More similar in sound to speaker", | |
interactive=True) | |
beta = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Beta", info="Defaults to 0.7 | Lower = More similar prosody at cost of stability", | |
interactive=True) | |
speed = gr.Slider(minimum=0.5, maximum=1.5, value=1, step=0.1, label="Speed of speech", | |
info="Defaults to 1", interactive=True) | |
with gr.Column(scale=1): | |
clbtn = gr.Button("Synthesize", variant="primary") | |
claudio = gr.Audio(interactive=False, label="Synthesized Audio", | |
waveform_options={'waveform_progress_color': '#FF593E'}) | |
clbtn.click(generate, inputs=[voice, inp, speed, alpha, beta, embscale, steps], outputs=[claudio], | |
concurrency_limit=15) | |
gr.Examples(examples=examples, | |
inputs=[voice, inp, speed, alpha, beta, embscale, steps], | |
outputs=[claudio], | |
fn=generate, | |
cache_examples=True,) | |
if __name__ == "__main__": | |
# demo.queue(api_open=False, max_size=15).launch(show_api=False) | |
clone.queue(api_open=False, max_size=15).launch(show_api=False) | |