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import io
import json
import os
import time
import uuid
from typing import Optional
import gradio as gr
import pandas as pd
import requests
from pydub import AudioSegment
from TTSs.base_tts import Base_TTS
class avaliable_voice_type:
语言: Optional[str] = ""
场景: Optional[str] = ""
音色名称: str
voice_type: str
时间戳支持: bool = False
支持情感与风格类型: Optional[str] = ""
支持语言类型: Optional[str] = ""
def __repr__(self):
data = self.__dict__
text = ""
text += f"{data['音色名称']}"
if data["语言"]:
text += f"——{data['语言']}"
if data["场景"]:
text += f"——{data['场景']}"
if data["支持情感与风格类型"]:
text += f"——{data['支持情感与风格类型']}"
if data["支持语言类型"]:
text += f"——{data['支持语言类型']}"
return text
class Volcengine_long_TTS(Base_TTS):
def get_name(self):
return '火山引擎精品长语音'
def __init__(self):
self.useful_voice = self.get_data_map()
self.emo_voice = {
"擎苍": "BV701_streaming",
"阳光青年": "BV123_streaming",
"反卷青年": "BV120_streaming",
"通用赘婿": "BV119_streaming",
"古风少御": "BV115_streaming",
"霸气青叔": "BV107_streaming",
"质朴青年": "BV100_streaming",
"温柔淑女": "BV104_streaming",
"开朗青年": "BV004_streaming",
"甜宠少御": "BV113_streaming",
"儒雅青年": "BV102_streaming"
}
def get_data_map(self, filename="voice_list.xlsx"):
path = os.path.join(os.path.dirname(os.path.abspath(__file__)), filename)
df = pd.read_excel(path)
df.fillna('', inplace=True)
useful_voice = {}
for index, row in df.iterrows():
data = avaliable_voice_type()
data.语言 = row['语言']
data.场景 = row['场景']
data.音色名称 = row['音色名称']
data.voice_type = row['voice_type']
data.时间戳支持 = row['时间戳']
data.支持情感与风格类型 = row['支持情感/风格类型']
data.支持语言类型 = row['支持语言类型']
useful_voice[str(data)] = data
return useful_voice
def update_dropdown(self, version):
if version == "普通版（不支持情感预测）":
voices = list(self.useful_voice.keys())
elif version == "情感预测版":
voices = list(self.emo_voice.keys())
change = gr.Dropdown(choices=voices, value=voices[0])
return change
def _get_config_page(self):
with gr.Group(visible=False) as config_volcengine:
voices = list(self.useful_voice.keys())
with gr.Row():
volcengine_appid = gr.Textbox(label="volcengine的appid（默认为环境变量值）",
placeholder="请输入volcengine的appid",
type="password",
interactive=True,
value=os.environ.get('VOLCENGINE_APPID', ''))
volcengine_access_token = gr.Textbox(label="volcengine的access_token（默认为环境变量值）",
placeholder="请输入volengine的access_token",
type="password",
interactive=True,
value=os.environ.get('VOLCENGINE_ACCESS_TOKEN', ''))
version = gr.Dropdown(choices=["普通版（不支持情感预测）", "情感预测版"], value="普通版（不支持情感预测）",
label="使用版本", interactive=True)
voice_type = gr.Dropdown(choices=voices, value=voices[0], label="音色选择", interactive=True)
with gr.Row():
speed_ratio = gr.Slider(minimum=0.2, maximum=3, value=1, step=0.1, label="语速",
interactive=True)
volume_ratio = gr.Slider(minimum=0.1, maximum=3, value=1, step=0.1, label="音量",
interactive=True)
pitch_ratio = gr.Slider(minimum=0.1, maximum=3, value=1, step=0.1, label="音高",
interactive=True)
with gr.Row():
emotion = gr.Textbox(label="情感/风格（还未适配）", placeholder="请输入情感", interactive=True)
language = gr.Textbox(label="语言类型（还未适配）", placeholder="请输入语言", interactive=True)
version.change(self.update_dropdown, inputs=[version], outputs=[voice_type])
inputs = [
volcengine_appid, version, volcengine_access_token, voice_type, speed_ratio,
volume_ratio, pitch_ratio
]
return config_volcengine, inputs
def _generate(self, text, appid, version, access_token, voice, speed_ratio,
volume_ratio, pitch_ratio):
host = "openspeech.bytedance.com"
if version == "普通版（不支持情感预测）":
submit_api_url = f"https://{host}/api/v1/tts_async/submit"
query_api_url = f"https://{host}/api/v1/tts_async/query"
header = {"Authorization": f"Bearer;{access_token}", "Resource-Id": "volc.tts_async.default"}
voice_type = self.useful_voice[voice].voice_type
elif version == "情感预测版":
submit_api_url = f"https://{host}/api/v1/tts_async_with_emotion/submit"
query_api_url = f"https://{host}/api/v1/tts_async_with_emotion/query"
header = {"Authorization": f"Bearer;{access_token}", "Resource-Id": "volc.tts_async.emotion"}
voice_type = self.emo_voice[voice]
request_json = {
"appid": appid,
"format": "mp3",
"reqid": str(uuid.uuid4()),
"voice_type": voice_type,
"speed": speed_ratio,
"volume": volume_ratio,
"pitch": pitch_ratio,
"text": text
}
resp = requests.post(submit_api_url, data=json.dumps(request_json), headers=header)
resp = resp.json()
if resp['task_status'] != 0:
raise Exception(resp)
task_id = resp['task_id']
# 每隔1秒查询一次任务状态，设置超时时间为300秒
query_json = {
"appid": appid,
"task_id": task_id
}
start_time = time.time()
while True:
time.sleep(2)
query_resp = requests.get(query_api_url, params=query_json, headers=header)
query_resp = query_resp.json()
if query_resp.get('task_status', 2) == 2:
raise Exception(query_resp)
elif query_resp.get('task_status') == 1:
break
if time.time() - start_time > 300:
raise TimeoutError("等待任务超时")
audio_url = query_resp['audio_url']
data = requests.get(audio_url).content
original_audio = AudioSegment.from_mp3(io.BytesIO(data))
return original_audio
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