File size: 7,938 Bytes
9f18b09 e80b05f 9f18b09 e80b05f 9f18b09 8826dde 9f18b09 8826dde 9f18b09 e51229d 9f18b09 64f43ed 4e61f80 9f18b09 e80b05f 9f18b09 8826dde 9f18b09 e80b05f 9f18b09 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 |
import warnings
warnings.filterwarnings("ignore")
# 外部库
import re
import requests
import argparse
import json
import os
import re
import tempfile
# import librosa
# import numpy as np
# import torch
# from torch import no_grad, LongTensor
# import commons
import gradio as gr
# import gradio.utils as gr_utils
# import gradio.processing_utils as gr_processing_utils
all_example = "Today is a wonderful day to build something people love!"
microsoft_model_list = [
"en-US-JennyMultilingualNeural",
"en-US-RyanMultilingualNeural",
"en-US-AndrewMultilingualNeural",
"en-US-AvaMultilingualNeural",
"en-US-BrianMultilingualNeural",
"en-US-EmmaMultilingualNeural",
"en-US-AlloyMultilingualNeural",
"en-US-EchoMultilingualNeural",
"en-US-FableMultilingualNeural",
"en-US-OnyxMultilingualNeural",
"en-US-NovaMultilingualNeural",
"en-US-ShimmerMultilingualNeural",
"en-US-AlloyMultilingualNeuralHD",
"en-US-EchoMultilingualNeuralHD",
"en-US-FableMultilingualNeuralHD",
"en-US-OnyxMultilingualNeuralHD",
"en-US-NovaMultilingualNeuralHD4",
"en-US-ShimmerMultilingualNeuralHD"
]
openai_model_list = [
"alloy",
"echo",
"fable",
"onyx",
"nova",
"shimmer"
]
eleven_voice_id = [
"21m00Tcm4TlvDq8ikWAM",
"29vD33N1CtxCmqQRPOHJ",
"2EiwWnXFnvU5JabPnv8n",
"5Q0t7uMcjvnagumLfvZi",
"AZnzlk1XvdvUeBnXmlld",
"CYw3kZ02Hs0563khs1Fj",
"D38z5RcWu1voky8WS1ja",
"EXAVITQu4vr4xnSDxMaL",
"ErXwobaYiN019PkySvjV",
"GBv7mTt0atIp3Br8iCZE",
"IKne3meq5aSn9XLyUdCD",
"JBFqnCBsd6RMkjVDRZzb",
"LcfcDJNUP1GQjkzn1xUU",
"MF3mGyEYCl7XYWbV9V6O",
"N2lVS1w4EtoT3dr4eOWO",
"ODq5zmih8GrVes37Dizd",
"SOYHLrjzK2X1ezoPC6cr",
"TX3LPaxmHKxFdv7VOQHJ",
"ThT5KcBeYPX3keUQqHPh",
"TxGEqnHWrfWFTfGW9XjX",
"VR6AewLTigWG4xSOukaG",
"XB0fDUnXU5powFXDhCwa",
"Xb7hH8MSUJpSbSDYk0k2",
"XrExE9yKIg1WjnnlVkGX",
"ZQe5CZNOzWyzPSCn5a3c",
"Zlb1dXrM653N07WRdFW3",
"bVMeCyTHy58xNoL34h3p",
"flq6f7yk4E4fJM5XTYuZ",
"g5CIjZEefAph4nQFvHAz",
"iP95p4xoKVk53GoZ742B",
"jBpfuIE2acCO8z3wKNLl",
"jsCqWAovK2LkecY7zXl4",
"nPczCjzI2devNBz1zQrb",
"oWAxZDx7w5VEj9dCyTzz",
"onwK4e9ZLuTAKqWW03F9",
"pFZP5JQG7iQjIQuC4Bku",
"pMsXgVXv3BLzUgSXRplE",
"pNInz6obpgDQGcFmaJgB",
"piTKgcLEGmPE4e6mEKli",
"pqHfZKP75CvOlQylNhV4",
"t0jbNlBVZ17f02VDIeMI",
"yoZ06aMxZJJ28mfd3POQ",
"z9fAnlkpzviPz146aGWa",
"zcAOhNBS3c14rBihAFp1",
"zrHiDhphv9ZnVXBqCLjz",
]
eleven_name = [
"Rachel",
"Drew",
"Clyde",
"Paul",
"Domi",
"Dave",
"Fin",
"Sarah",
"Antoni",
"Thomas",
"Charlie",
"George",
"Emily",
"Elli",
"Callum",
"Patrick",
"Harry",
"Liam",
"Dorothy",
"Josh",
"Arnold",
"Charlotte",
"Alice",
"Matilda",
"James",
"Joseph",
"Jeremy",
"Michael",
"Ethan",
"Chris",
"Gigi",
"Freya",
"Brian",
"Grace",
"Daniel",
"Lily",
"Serena",
"Adam",
"Nicole",
"Bill",
"Jessie",
"Sam",
"Glinda",
"Giovanni",
"Mimi",
]
eleven_id_model_name_dict = dict(zip(eleven_name, eleven_voice_id))
def openai(text, name):
headers = {
'Authorization': 'Bearer ' + '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',
'Content-Type': 'application/json',
}
json_data = {
'model': 'tts-1-hd',
'input': text,
'voice': name,
}
response = requests.post('https://api.openai.com/v1/audio/speech', headers=headers, json=json_data)
# Note: json_data will not be serialized by requests
# exactly as it was in the original request.
#data = '{\n "model": "tts-1",\n "input": "The quick brown fox jumped over the lazy dog.",\n "voice": "alloy"\n }'
#response = requests.post('https://api.openai.com/v1/audio/speech', headers=headers, data=data)
return "Success", response
def elevenlabs(text,name):
url = f"https://api.elevenlabs.io/v1/text-to-speech/{eleven_id_model_name_dict[name]}"
CHUNK_SIZE = 1024
#url = "https://api.elevenlabs.io/v1/text-to-speech/<voice-id>"
headers = {
"Accept": "audio/mpeg",
"Content-Type": "application/json",
"xi-api-key": "a3391f0e3ff8472b61978dbb70ccc6fe"
}
data = {
"text": text,
"model_id": "eleven_monolingual_v1",
"voice_settings": {
"stability": 0.5,
"similarity_boost": 0.5
}
}
response = requests.post(url, json=data, headers=headers)
# with open('output.mp3', 'wb') as f:
# for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
# if chunk:
# f.write(chunk)
return "Success", response.content
def microsoft(text, name, style="Neural"):
"""
:param text:
:param name:
:param style:
:return:
"""
headers = {
'Ocp-Apim-Subscription-Key': '1f1ef0ce53b84261be94fab81df7e628',
'Content-Type': 'application/ssml+xml',
'X-Microsoft-OutputFormat': 'audio-16khz-128kbitrate-mono-mp3',
'User-Agent': 'curl',
}
data = ("<speak version='1.0' xml:lang='en-US'>"
f"<voice xml:lang='en-US' name='{name}'>" # xml:gender='Female'
f"{text}"
"</voice>"
"</speak>")
response = requests.post(
'https://japaneast.tts.speech.microsoft.com/cognitiveservices/v1',
headers=headers,
data=data,
)
return "Success", response.content
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--device', type=str, default='cuda')
parser.add_argument("--share", action="store_true", default=True, help="share gradio app")
parser.add_argument("--port", type=int, default=8081, help="port")
parser.add_argument('--model_info_path', type=str, default='/gluster/speech_data/info.json')
args = parser.parse_args()
app = gr.Blocks()
with app:
gr.Markdown("## English TTS Demo")
with gr.Tabs():
with gr.TabItem("11Labs"):
tts_input1 = gr.TextArea(label="Text", value=all_example)
tts_input2 = gr.Dropdown(eleven_name, label="name")
tts_submit = gr.Button("Generate", variant="primary")
tts_output1 = gr.Textbox(label="Output Message")
tts_output2 = gr.Audio(label="Output Audio")
tts_submit.click(elevenlabs, [tts_input1, tts_input2],
[tts_output1, tts_output2])
with gr.TabItem("微软"):
tts_input1 = gr.TextArea(label="Text", value=all_example)
tts_input2 = gr.Dropdown(microsoft_model_list, label="name")
tts_submit = gr.Button("Generate", variant="primary")
tts_output1 = gr.Textbox(label="Output Message")
tts_output2 = gr.Textbox(label="Output Audio")
#tts_output2 = gr.Audio(label="Output Audio")
tts_submit.click(microsoft, [tts_input1, tts_input2],
[tts_output1, tts_output2])
with gr.TabItem("openai"):
tts_input1 = gr.TextArea(label="Text", value=all_example)
tts_input2 = gr.Dropdown(openai_model_list, label="name")
tts_submit = gr.Button("Generate", variant="primary")
tts_output1 = gr.Textbox(label="Output Message")
tts_output2 = gr.Audio(label="Output Audio")
tts_submit.click(openai, [tts_input1, tts_input2],
[tts_output1, tts_output2])
# app.queue(max_size=10)
app.launch(share=True)
# _, audio = openai(all_example,'alloy')
# print(audio)
# with open("test99.mp3", "wb") as f:
# f.write(audio.content)
|