xVASynth-TTS / app.py
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import os
import sys
import time
import requests
import json
from subprocess import Popen, PIPE
import threading
from huggingface_hub import hf_hub_download
import gradio as gr
# try:
import resources.app.no_server as xvaserver
# except:
# print('server.log contents:')
# with open('resources/app/server.log', 'r') as f:
# print(f.read())
hf_model_name = "Pendrokar/xvapitch_nvidia"
hf_cache_models_path = '/home/user/.cache/huggingface/hub/models--Pendrokar--xvapitch_nvidia/snapshots/61b10e60b22bc21c1e072f72f1108b9c2b21e94c/'
models_path = '/home/user/.cache/huggingface/hub/models--Pendrokar--xvapitch_nvidia/snapshots/61b10e60b22bc21c1e072f72f1108b9c2b21e94c/'
# FIXME: currently hardcoded in DeepMoji code
# try:
# os.symlink('/home/user/.cache/huggingface/hub/models--Pendrokar--TorchMoji/snapshots/58217568daaf64d3621245dd5c88c94e651a08d6', '/home/user/app/resources/app/plugins/deepmoji_plugings/model', target_is_directory=True)
# except:
# print('Failed to create symlink to DeepMoji model, may already be there.')
voice_models = [
("Male #6671", "ccby_nvidia_hifi_6671_M"),
("Male #6670", "ccby_nvidia_hifi_6670_M"),
("Male #9017", "ccby_nvidia_hifi_9017_M"),
("Male #6097", "ccby_nvidia_hifi_6097_M"),
("Female #92", "ccby_nvidia_hifi_92_F"),
("Female #11697", "ccby_nvidia_hifi_11697_F"),
("Female #12787", "ccby_nvidia_hifi_12787_F"),
("Female #11614", "ccby_nv_hifi_11614_F"),
("Female #8051", "ccby_nvidia_hifi_8051_F"),
("Female #9136", "ccby_nvidia_hifi_9136_F"),
]
current_voice_model = None
base_speaker_emb = ''
# order ranked by similarity to English due to the xVASynth's use of ARPAbet instead of IPA
languages = [
("🇬🇧 EN", "en"),
("🇩🇪 DE", "de"),
("🇪🇸 ES", "es"),
("🇮🇹 IT", "it"),
("🇳🇱 NL", "nl"),
("🇵🇹 PT", "pt"),
("🇵🇱 PL", "pl"),
("🇷🇴 RO", "ro"),
("🇸🇪 SV", "sv"),
("🇩🇰 DA", "da"),
("🇫🇮 FI", "fi"),
("🇭🇺 HU", "hu"),
("🇬🇷 EL", "el"),
("🇫🇷 FR", "fr"),
("🇷🇺 RU", "ru"),
("🇺🇦 UK", "uk"),
("🇹🇷 TR", "tr"),
("🇸🇦 AR", "ar"),
("🇮🇳 HI", "hi"),
("🇯🇵 JP", "jp"),
("🇰🇷 KO", "ko"),
("🇨🇳 ZH", "zh"),
("🇻🇳 VI", "vi"),
("🇻🇦 LA", "la"),
("HA", "ha"),
("SW", "sw"),
("🇳🇬 YO", "yo"),
("WO", "wo"),
]
# Translated from English by DeepMind's Gemini Pro
default_text = {
"ar": "هذا هو صوتي.",
"da": "Sådan lyder min stemme.",
"de": "So klingt meine Stimme.",
"el": "Έτσι ακούγεται η φωνή μου.",
"en": "This is what my voice sounds like.",
"es": "Así suena mi voz.",
"fi": "Näin ääneni kuulostaa.",
"fr": "Voici à quoi ressemble ma voix.",
"ha": "Wannan ne muryata ke.",
"hi": "यह मेरी आवाज़ कैसी लगती है।",
"hu": "Így hangzik a hangom.",
"it": "Così suona la mia voce.",
"jp": "これが私の声です。",
"ko": "여기 제 목소리가 어떤지 들어보세요.",
"la": "Haec est vox mea sonans.",
"nl": "Dit is hoe mijn stem klinkt.",
"pl": "Tak brzmi mój głos.",
"pt": "É assim que minha voz soa.",
"ro": "Așa sună vocea mea.",
"ru": "Вот как звучит мой голос.",
"sv": "Såhär låter min röst.",
"sw": "Sauti yangu inasikika hivi.",
"tr": "Benim sesimin sesi böyle.",
"uk": "Ось як звучить мій голос.",
"vi": "Đây là giọng nói của tôi.",
"wo": "Ndox li neen xewnaal ma.",
"yo": "Ìyí ni ohùn mi ńlá.",
"zh": "这是我的声音。",
}
def run_xvaserver():
# start the process without waiting for a response
print('Running xVAServer subprocess...\n')
xvaserver = Popen(['python', f'{os.path.dirname(os.path.abspath(__file__))}/resources/app/server.py'], stdout=PIPE, stderr=PIPE, cwd=f'{os.path.dirname(os.path.abspath(__file__))}/resources/app/')
# Wait for a moment to ensure the server starts up
time.sleep(10)
# Check if the server is running
if xvaserver.poll() is not None:
print("Web server failed to start.")
sys.exit(0)
# contact local xVASynth server
print('Attempting to connect to xVASynth...')
try:
response = requests.get('http://0.0.0.0:8008')
response.raise_for_status() # If the response contains an HTTP error status code, raise an exception
except requests.exceptions.RequestException as err:
print('Failed to connect!')
return
print('xVAServer running on port 8008')
# load default model
load_model("ccby_nvidia_hifi_6671_M")
# Wait for the process to exit
xvaserver.wait()
def load_model(voice_model_name):
model_path = models_path + voice_model_name
model_type = 'xVAPitch'
language = 'en'
data = {
'outputs': None,
'version': '3.0',
'model': model_path,
'modelType': model_type,
'base_lang': language,
'pluginsContext': '{}',
}
embs = base_speaker_emb
print('Loading voice model...')
try:
json_data = xvaserver.loadModel(data)
current_voice_model = voice_model_name
with open(model_path + '.json', 'r', encoding='utf-8') as f:
voice_model_json = json.load(f)
embs = voice_model_json['games'][0]['base_speaker_emb']
except requests.exceptions.RequestException as err:
print(f'FAILED to load voice model: {err}')
return embs
def predict(
input_text,
voice,
lang,
pacing,
pitch,
energy,
anger,
happy,
sad,
surprise,
use_deepmoji
):
# grab only the first 1000 characters
input_text = input_text[:1000]
# load voice model if not the current model
if (current_voice_model != voice):
base_speaker_emb = load_model(voice)
model_type = 'xVAPitch'
pace = pacing if pacing else 1.0
save_path = '/tmp/xvapitch_audio_sample.wav'
language = lang
use_sr = 0
use_cleanup = 0
pluginsContext = {}
pluginsContext["mantella_settings"] = {
"emAngry": (anger if anger > 0 else 0),
"emHappy": (happy if happy > 0 else 0),
"emSad": (sad if sad > 0 else 0),
"emSurprise": (surprise if surprise > 0 else 0),
"run_model": use_deepmoji
}
data = {
'pluginsContext': json.dumps(pluginsContext),
'modelType': model_type,
# pad with whitespaces as a workaround to avoid cutoffs
'sequence': input_text.center(len(input_text) + 2, ' '),
'pace': pace,
'outfile': save_path,
'vocoder': 'n/a',
'base_lang': language,
'base_emb': base_speaker_emb,
'useSR': use_sr,
'useCleanup': use_cleanup,
}
print('Synthesizing...')
try:
json_data = xvaserver.synthesize(data)
# response = requests.post('http://0.0.0.0:8008/synthesize', json=data, timeout=60)
# response.raise_for_status() # If the response contains an HTTP error status code, raise an exception
# json_data = json.loads(response.text)
except requests.exceptions.RequestException as err:
print('FAILED to synthesize: {err}')
save_path = ''
response = {'text': '{"message": "Failed"}'}
json_data = {
'arpabet': ['Failed'],
'durations': [0],
'em_anger': anger,
'em_happy': happy,
'em_sad': sad,
'em_surprise': surprise,
}
# print('server.log contents:')
# with open('resources/app/server.log', 'r') as f:
# print(f.read())
arpabet_html = '<h6>ARPAbet & Phoneme lengths</h6>'
arpabet_symbols = json_data['arpabet'].split('|')
utter_time = 0
for symb_i in range(len(json_data['durations'])):
# skip PAD symbol
if (arpabet_symbols[symb_i] == '<PAD>'):
continue
length = float(json_data['durations'][symb_i])
arpa_length = str(round(length/2, 1))
arpabet_html += '<strong\
class="arpabet"\
style="padding: 0 '\
+ str(arpa_length)\
+'em"'\
+f" title=\"{utter_time} + {length}\""\
+'>'\
+ arpabet_symbols[symb_i]\
+ '</strong> '
utter_time += round(length, 1)
return [
save_path,
arpabet_html,
round(json_data['em_angry'][0], 2),
round(json_data['em_happy'][0], 2),
round(json_data['em_sad'][0], 2),
round(json_data['em_surprise'][0], 2),
json_data
]
input_textbox = gr.Textbox(
label="Input Text",
value="This is what my voice sounds like.",
info="Also accepts ARPAbet symbols placed within {} brackets.",
lines=1,
max_lines=5,
autofocus=True
)
pacing_slider = gr.Slider(0.5, 2.0, value=1.0, step=0.1, label="Duration")
pitch_slider = gr.Slider(0, 1.0, value=0.5, step=0.05, label="Pitch", visible=False)
energy_slider = gr.Slider(0.1, 1.0, value=1.0, step=0.05, label="Energy", visible=False)
anger_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😠 Anger", info="Tread lightly beyond 0.9")
happy_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😃 Happiness", info="Tread lightly beyond 0.7")
sad_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😭 Sadness", info="Duration increased when beyond 0.2")
surprise_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😮 Surprise", info="Does not play well with Happiness with either being beyond 0.3")
voice_radio = gr.Radio(
voice_models,
value="ccby_nvidia_hifi_6671_M",
label="Voice",
info="NVIDIA HIFI CC-BY-4.0 xVAPitch voice model"
)
def set_default_text(lang, deepmoji_checked):
# DeepMoji only works on English Text
# checkbox_enabled = True
# if lang != 'en':
# checkbox_enabled = False
if lang == 'en':
checkbox_enabled = gr.Checkbox(
label="Use DeepMoji",
info="Auto adjust emotional values",
value=deepmoji_checked,
interactive=True
)
else:
checkbox_enabled = gr.Checkbox(
label="Use DeepMoji",
info="Works only with English!",
value=False,
interactive=False
)
return default_text[lang], checkbox_enabled # Return the modified textbox (important for Blocks)
def reset_em_sliders(
deepmoji_enabled,
anger,
happy,
sad,
surprise
):
if (deepmoji_enabled):
return (0, 0, 0, 0)
else:
return (
anger,
happy,
sad,
surprise
)
def toggle_deepmoji(
checked,
anger,
happy,
sad,
surprise
):
if checked:
return (0, 0, 0, 0)
else:
return (
anger,
happy,
sad,
surprise
)
language_radio = gr.Radio(
languages,
value="en",
label="Language",
info="Will be more monotone and have an English accent. Tested mostly by a native Briton."
)
_DESCRIPTION = '''
<div>
<a style="display:inline-block;" href="https://github.com/DanRuta/xVA-Synth"><img src='https://img.shields.io/github/stars/DanRuta/xVA-Synth?style=social'/></a>
<a style="display:inline-block; margin-left: .5em" href="https://discord.gg/nv7c6E2TzV"><img src='https://img.shields.io/discord/794590496202293278.svg?label=&logo=discord&logoColor=ffffff&color=7389D8&labelColor=6A7EC2'/></a>
<span style="display: inline-block;margin-left: .5em;vertical-align: top;"><a href="https://huggingface.co/spaces/Pendrokar/xVASynth?duplicate=true" style="" target="_blank"><img style="margin-bottom: 0em;display: inline;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for a personal CPU-run</span>
</div>
'''
with gr.Blocks(css=".arpabet {display: inline-block; background-color: gray; border-radius: 5px; font-size: 120%; margin: 0.1em 0}") as demo:
gr.Markdown("# xVASynth TTS")
gr.HTML(label="description", value=_DESCRIPTION)
with gr.Row(): # Main row for inputs and language selection
with gr.Column(): # Input column
input_textbox = gr.Textbox(
label="Input Text",
value="This is what my voice sounds like.",
info="Also accepts ARPAbet symbols placed within {} brackets.",
lines=1,
max_lines=5,
autofocus=True
)
language_radio = gr.Radio(
languages,
value="en",
label="Language",
info="Will be more monotone and have an English accent. Tested mostly by a native Briton."
)
pacing_slider = gr.Slider(0.5, 2.0, value=1.0, step=0.1, label="Duration")
with gr.Column(): # Control column
voice_radio = gr.Radio(
voice_models,
value="ccby_nvidia_hifi_6671_M",
label="Voice",
info="NVIDIA HIFI CC-BY-4.0 xVAPitch voice model"
)
pitch_slider = gr.Slider(0, 1.0, value=0.5, step=0.05, label="Pitch", visible=False)
energy_slider = gr.Slider(0.1, 1.0, value=1.0, step=0.05, label="Energy", visible=False)
with gr.Row(): # Main row for inputs and language selection
with gr.Column(): # Input column
anger_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😠 Anger", info="Tread lightly beyond 0.9")
sad_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😭 Sadness", info="Duration increased when beyond 0.2")
with gr.Column(): # Input column
happy_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😃 Happiness", info="Tread lightly beyond 0.7")
surprise_slider = gr.Slider(0, 1.0, value=0, step=0.05, label="😮 Surprise", info="Can oversaturate Happiness")
deepmoji_checkbox = gr.Checkbox(label="Use DeepMoji", info="Auto adjust emotional values", value=True)
# Event handling using click
btn = gr.Button("Generate", variant="primary")
with gr.Row(): # Main row for inputs and language selection
with gr.Column(): # Input column
output_wav = gr.Audio(
label="22kHz audio output",
type="filepath",
editable=False,
autoplay=True
)
with gr.Column(): # Input column
output_arpabet = gr.HTML(label="ARPAbet")
btn.click(
fn=predict,
inputs=[
input_textbox,
voice_radio,
language_radio,
pacing_slider,
pitch_slider,
energy_slider,
anger_slider,
happy_slider,
sad_slider,
surprise_slider,
deepmoji_checkbox
],
outputs=[
output_wav,
output_arpabet,
anger_slider,
happy_slider,
sad_slider,
surprise_slider,
# xVAServer response
gr.Textbox(visible=False)
]
)
input_textbox.submit(
fn=predict,
inputs=[
input_textbox,
voice_radio,
language_radio,
pacing_slider,
pitch_slider,
energy_slider,
anger_slider,
happy_slider,
sad_slider,
surprise_slider,
deepmoji_checkbox
],
outputs=[
output_wav,
output_arpabet,
anger_slider,
happy_slider,
sad_slider,
surprise_slider,
# xVAServer response
gr.Textbox(visible=False)
]
)
language_radio.change(
set_default_text,
inputs=[language_radio, deepmoji_checkbox],
outputs=[input_textbox, deepmoji_checkbox]
)
deepmoji_checkbox.change(
toggle_deepmoji,
inputs=[
deepmoji_checkbox,
anger_slider,
happy_slider,
sad_slider,
surprise_slider
],
outputs=[
anger_slider,
happy_slider,
sad_slider,
surprise_slider
]
)
input_textbox.change(
reset_em_sliders,
inputs=[
deepmoji_checkbox,
anger_slider,
happy_slider,
sad_slider,
surprise_slider
],
outputs=[
anger_slider,
happy_slider,
sad_slider,
surprise_slider
]
)
voice_radio.change(
reset_em_sliders,
inputs=[
deepmoji_checkbox,
anger_slider,
happy_slider,
sad_slider,
surprise_slider
],
outputs=[
anger_slider,
happy_slider,
sad_slider,
surprise_slider
]
)
if __name__ == "__main__":
# Run the web server in a separate thread
# print('Attempting to connect to local xVASynth server...')
# try:
# response = requests.get('http://0.0.0.0:8008')
# response.raise_for_status() # If the response contains an HTTP error status code, raise an exception
# except requests.exceptions.RequestException as err:
# print('Failed to connect to xVASynth!')
# web_server_thread = threading.Thread(target=run_xvaserver)
# print('Starting xVAServer thread')
# web_server_thread.start()
print('running Gradio interface')
demo.launch()
# Wait for the web server thread to finish (shouldn't be reached in normal execution)
# web_server_thread.join()