webui.py
Browse files- webui (1).py +183 -0
webui (1).py
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# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Liu Yue)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import sys
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ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.append('{}/third_party/Matcha-TTS'.format(ROOT_DIR))
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import argparse
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import gradio as gr
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import numpy as np
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import torch
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import torchaudio
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import random
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import librosa
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from cosyvoice.cli.cosyvoice import CosyVoice
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from cosyvoice.utils.file_utils import load_wav, speed_change, logging
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def generate_seed():
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seed = random.randint(1, 100000000)
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return {
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"__type__": "update",
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"value": seed
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}
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def set_all_random_seed(seed):
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random.seed(seed)
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np.random.seed(seed)
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torch.manual_seed(seed)
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torch.cuda.manual_seed_all(seed)
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max_val = 0.8
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def postprocess(speech, top_db=60, hop_length=220, win_length=440):
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speech, _ = librosa.effects.trim(
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speech, top_db=top_db,
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frame_length=win_length,
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hop_length=hop_length
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)
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if speech.abs().max() > max_val:
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speech = speech / speech.abs().max() * max_val
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speech = torch.concat([speech, torch.zeros(1, int(target_sr * 0.2))], dim=1)
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return speech
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inference_mode_list = ['预训练音色', '3s极速复刻', '跨语种复刻', '自然语言控制']
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instruct_dict = {'预训练音色': '1. 选择预训练音色\n2. 点击生成音频按钮',
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'3s极速复刻': '1. 选择prompt音频文件,或录入prompt音频,注意不超过30s,若同时提供,优先选择prompt音频文件\n2. 输入prompt文本\n3. 点击生成音频按钮',
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'跨语种复刻': '1. 选择prompt音频文件,或录入prompt音频,注意不超过30s,若同时提供,优先选择prompt音频文件\n2. 点击生成音频按钮',
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'自然语言控制': '1. 选择预训练音色\n2. 输入instruct文本\n3. 点击生成音频按钮'}
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stream_mode_list = [('否', False), ('是', True)]
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def change_instruction(mode_checkbox_group):
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return instruct_dict[mode_checkbox_group]
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def generate_audio(tts_text, mode_checkbox_group, sft_dropdown, prompt_text, prompt_wav_upload, prompt_wav_record, instruct_text, seed, stream, speed_factor):
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if prompt_wav_upload is not None:
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prompt_wav = prompt_wav_upload
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elif prompt_wav_record is not None:
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prompt_wav = prompt_wav_record
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else:
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prompt_wav = None
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# if instruct mode, please make sure that model is iic/CosyVoice-300M-Instruct and not cross_lingual mode
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if mode_checkbox_group in ['自然语言控制']:
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if cosyvoice.frontend.instruct is False:
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gr.Warning('您正在使用自然语言控制模式, {}模型不支持此模式, 请使用iic/CosyVoice-300M-Instruct模型'.format(args.model_dir))
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return (target_sr, default_data)
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if instruct_text == '':
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gr.Warning('您正在使用自然语言控制模式, 请输入instruct文本')
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return (target_sr, default_data)
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if prompt_wav is not None or prompt_text != '':
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gr.Info('您正在使用自然语言控制模式, prompt音频/prompt文本会被忽略')
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# if cross_lingual mode, please make sure that model is iic/CosyVoice-300M and tts_text prompt_text are different language
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if mode_checkbox_group in ['跨语种复刻']:
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if cosyvoice.frontend.instruct is True:
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gr.Warning('您正在使用跨语种复刻模式, {}模型不支持此模式, 请使用iic/CosyVoice-300M模型'.format(args.model_dir))
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return (target_sr, default_data)
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if instruct_text != '':
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gr.Info('您正在使用跨语种复刻模式, instruct文本会被忽略')
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if prompt_wav is None:
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gr.Warning('您正在使用跨语种复刻模式, 请提供prompt音频')
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return (target_sr, default_data)
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gr.Info('您正在使用跨语种复刻模式, 请确保合成文本和prompt文本为不同语言')
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# if in zero_shot cross_lingual, please make sure that prompt_text and prompt_wav meets requirements
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if mode_checkbox_group in ['3s极速复刻', '跨语种复刻']:
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if prompt_wav is None:
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gr.Warning('prompt音频为空,您是否忘记输入prompt音频?')
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return (target_sr, default_data)
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if torchaudio.info(prompt_wav).sample_rate < prompt_sr:
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gr.Warning('prompt音频采样率{}低于{}'.format(torchaudio.info(prompt_wav).sample_rate, prompt_sr))
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return (target_sr, default_data)
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# sft mode only use sft_dropdown
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if mode_checkbox_group in ['预训练音色']:
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if instruct_text != '' or prompt_wav is not None or prompt_text != '':
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gr.Info('您正在使用预训练音色模式,prompt文本/prompt音频/instruct文本会被忽略!')
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# zero_shot mode only use prompt_wav prompt text
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if mode_checkbox_group in ['3s极速复刻']:
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if prompt_text == '':
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gr.Warning('prompt文本为空,您是否忘记输入prompt文本?')
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return (target_sr, default_data)
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if instruct_text != '':
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gr.Info('您正在使用3s极速复刻模式,预训练音色/instruct文本会被忽略!')
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if mode_checkbox_group == '预训练音色':
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logging.info('get sft inference request')
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set_all_random_seed(seed)
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for i in cosyvoice.inference_sft(tts_text, sft_dropdown, stream=stream):
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yield (target_sr, i['tts_speech'].numpy().flatten())
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elif mode_checkbox_group == '3s极速复刻':
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logging.info('get zero_shot inference request')
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prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr))
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set_all_random_seed(seed)
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for i in cosyvoice.inference_zero_shot(tts_text, prompt_text, prompt_speech_16k, stream=stream):
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yield (target_sr, i['tts_speech'].numpy().flatten())
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elif mode_checkbox_group == '跨语种复刻':
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logging.info('get cross_lingual inference request')
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prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr))
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set_all_random_seed(seed)
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for i in cosyvoice.inference_cross_lingual(tts_text, prompt_speech_16k, stream=stream):
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yield (target_sr, i['tts_speech'].numpy().flatten())
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else:
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logging.info('get instruct inference request')
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set_all_random_seed(seed)
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for i in cosyvoice.inference_instruct(tts_text, sft_dropdown, instruct_text, stream=stream):
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yield (target_sr, i['tts_speech'].numpy().flatten())
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def main():
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with gr.Blocks() as demo:
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gr.Markdown("### 代码库 [CosyVoice](https://github.com/FunAudioLLM/CosyVoice) 预训练模型 [CosyVoice-300M](https://www.modelscope.cn/models/iic/CosyVoice-300M) [CosyVoice-300M-Instruct](https://www.modelscope.cn/models/iic/CosyVoice-300M-Instruct) [CosyVoice-300M-SFT](https://www.modelscope.cn/models/iic/CosyVoice-300M-SFT)")
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gr.Markdown("#### 请输入需要合成的文本,选择推理模式,并按照提示步骤进行操作")
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tts_text = gr.Textbox(label="输入合成文本", lines=1, value="我是通义实验室语音团队全新推出的生成式语音大模型,提供舒适自然的语音合成能力。")
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speed_factor = gr.Slider(minimum=0.25, maximum=4, step=0.05, label="语速调节", value=1.0, interactive=True)
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with gr.Row():
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mode_checkbox_group = gr.Radio(choices=inference_mode_list, label='选择推理模式', value=inference_mode_list[0])
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instruction_text = gr.Text(label="操作步骤", value=instruct_dict[inference_mode_list[0]], scale=0.5)
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sft_dropdown = gr.Dropdown(choices=sft_spk, label='选择预训练音色', value=sft_spk[0], scale=0.25)
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stream = gr.Radio(choices=stream_mode_list, label='是否流式推理', value=stream_mode_list[0][1])
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with gr.Column(scale=0.25):
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seed_button = gr.Button(value="\U0001F3B2")
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seed = gr.Number(value=0, label="随机推理种子")
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with gr.Row():
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prompt_wav_upload = gr.Audio(sources='upload', type='filepath', label='选择prompt音频文件,注意采样率不低于16khz')
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prompt_wav_record = gr.Audio(sources='microphone', type='filepath', label='录制prompt音频文件')
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prompt_text = gr.Textbox(label="输入prompt文本", lines=1, placeholder="请输入prompt文本,需与prompt音频内容一致,暂时不支持自动识别...", value='')
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instruct_text = gr.Textbox(label="输入instruct文本", lines=1, placeholder="请输入instruct文本.", value='')
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generate_button = gr.Button("生成音频")
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audio_output = gr.Audio(label="合成音频", autoplay=True, streaming=True)
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seed_button.click(generate_seed, inputs=[], outputs=seed)
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generate_button.click(generate_audio,
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inputs=[tts_text, mode_checkbox_group, sft_dropdown, prompt_text, prompt_wav_upload, prompt_wav_record, instruct_text, seed, stream, speed_factor],
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outputs=[audio_output])
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mode_checkbox_group.change(fn=change_instruction, inputs=[mode_checkbox_group], outputs=[instruction_text])
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demo.queue(max_size=4, default_concurrency_limit=2)
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demo.launch(server_name='0.0.0.0', server_port=args.port,share=True)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--port',
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type=int,
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default=8000)
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parser.add_argument('--model_dir',
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type=str,
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default='pretrained_models/CosyVoice-300M',
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help='local path or modelscope repo id')
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args = parser.parse_args()
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cosyvoice = CosyVoice(args.model_dir)
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sft_spk = cosyvoice.list_avaliable_spks()
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prompt_sr, target_sr = 16000, 22050
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default_data = np.zeros(target_sr)
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main()
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