# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu) # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import sys ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) sys.path.append('{}/third_party/AcademiCodec'.format(ROOT_DIR)) sys.path.append('{}/third_party/Matcha-TTS'.format(ROOT_DIR)) import argparse import gradio as gr import numpy as np import torch import torchaudio import random import librosa import logging logging.getLogger('matplotlib').setLevel(logging.WARNING) from cosyvoice.cli.cosyvoice import CosyVoice from cosyvoice.utils.file_utils import load_wav logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(message)s') def generate_seed(): seed = random.randint(1, 100000000) return { "__type__": "update", "value": seed } def set_all_random_seed(seed): random.seed(seed) np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed_all(seed) max_val = 0.8 def postprocess(speech, top_db=60, hop_length=220, win_length=440): speech, _ = librosa.effects.trim( speech, top_db=top_db, frame_length=win_length, hop_length=hop_length ) if speech.abs().max() > max_val: speech = speech / speech.abs().max() * max_val speech = torch.concat([speech, torch.zeros(1, int(target_sr * 0.2))], dim=1) return speech inference_mode_list = ['预训练音色', '3s极速复刻', '跨语种复刻', '自然语言控制'] instruct_dict = {'预训练音色': '1. 选择预训练音色\n2.点击生成音频按钮', '3s极速复刻': '1. 选择prompt音频文件，或录入prompt音频，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', '跨语种复刻': '1. 选择prompt音频文件，或录入prompt音频，若同时提供，优先选择prompt音频文件\n2.点击生成音频按钮', '自然语言控制': '1. 输入instruct文本\n2.点击生成音频按钮'} def change_instruction(mode_checkbox_group): return instruct_dict[mode_checkbox_group] def generate_audio(tts_text, mode_checkbox_group, sft_dropdown, prompt_text, prompt_wav_upload, prompt_wav_record, instruct_text, seed): if prompt_wav_upload is not None: prompt_wav = prompt_wav_upload elif prompt_wav_record is not None: prompt_wav = prompt_wav_record else: prompt_wav = None # if instruct mode, please make sure that model is speech_tts/CosyVoice-300M-Instruct and not cross_lingual mode if mode_checkbox_group in ['自然语言控制']: if cosyvoice.frontend.instruct is False: 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speech_tts/CosyVoice-300M-Instruct模型'.format(args.model_dir)) return (target_sr, default_data) if instruct_text == '': gr.Warning('您正在使用自然语言控制模式, 请输入instruct文本') return (target_sr, default_data) if prompt_wav is not None or prompt_text != '': 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') # if cross_lingual mode, please make sure that model is speech_tts/CosyVoice-300M and tts_text prompt_text are different language if mode_checkbox_group in ['跨语种复刻']: if cosyvoice.frontend.instruct is True: 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speech_tts/CosyVoice-300M模型'.format(args.model_dir)) return (target_sr, default_data) if instruct_text != '': gr.Info('您正在使用跨语种复刻模式, instruct文本会被忽略') if prompt_wav is None: gr.Warning('您正在使用跨语种复刻模式, 请提供prompt音频') return (target_sr, default_data) 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') # if in zero_shot cross_lingual, please make sure that prompt_text and prompt_wav meets requirements if mode_checkbox_group in ['3s极速复刻', '跨语种复刻']: if prompt_wav is None: gr.Warning('prompt音频为空，您是否忘记输入prompt音频？') return (target_sr, default_data) if torchaudio.info(prompt_wav).sample_rate < prompt_sr: gr.Warning('prompt音频采样率{}低于{}'.format(torchaudio.info(prompt_wav).sample_rate, prompt_sr)) return (target_sr, default_data) # sft mode only use sft_dropdown if mode_checkbox_group in ['预训练音色']: if instruct_text != '' or prompt_wav is not None or prompt_text != '': 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！') # zero_shot mode only use prompt_wav prompt text if mode_checkbox_group in ['3s极速复刻']: if prompt_text == '': gr.Warning('prompt文本为空，您是否忘记输入prompt文本？') return (target_sr, default_data) if instruct_text != '': 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！') if mode_checkbox_group == '预训练音色': logging.info('get sft inference request') set_all_random_seed(seed) output = cosyvoice.inference_sft(tts_text, sft_dropdown) elif mode_checkbox_group == '3s极速复刻': logging.info('get zero_shot inference request') prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr)) set_all_random_seed(seed) output = cosyvoice.inference_zero_shot(tts_text, prompt_text, prompt_speech_16k) elif mode_checkbox_group == '跨语种复刻': logging.info('get cross_lingual inference request') prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr)) set_all_random_seed(seed) output = cosyvoice.inference_cross_lingual(tts_text, prompt_speech_16k) else: logging.info('get instruct inference request') set_all_random_seed(seed) output = cosyvoice.inference_instruct(tts_text, sft_dropdown, instruct_text) audio_data = output['tts_speech'].numpy().flatten() return (target_sr, audio_data) def main(): with gr.Blocks() as demo: gr.Markdown("### 代码库 [CosyVoice](https://github.com/FunAudioLLM/CosyVoice) 预训练模型 [CosyVoice-300M](https://www.modelscope.cn/models/speech_tts/CosyVoice-300M) [CosyVoice-300M-Instruct](https://www.modelscope.cn/models/speech_tts/CosyVoice-300M-Instruct) [CosyVoice-300M-SFT](https://www.modelscope.cn/models/speech_tts/CosyVoice-300M-SFT)") 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") 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。") with gr.Row(): mode_checkbox_group = gr.Radio(choices=inference_mode_list, label='选择推理模式', value=inference_mode_list[0]) instruction_text = gr.Text(label="操作步骤", value=instruct_dict[inference_mode_list[0]], scale=0.5) sft_dropdown = gr.Dropdown(choices=sft_spk, label='选择预训练音色', value=sft_spk[0], scale=0.25) with gr.Column(scale=0.25): seed_button = gr.Button(value="\U0001F3B2") seed = gr.Number(value=0, label="随机推理种子") with gr.Row(): 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') prompt_wav_record = gr.Audio(sources='microphone', type='filepath', label='录制prompt音频文件') 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='') instruct_text = gr.Textbox(label="输入instruct文本", lines=1, placeholder="请输入instruct文本.", value='') generate_button = gr.Button("生成音频") audio_output = gr.Audio(label="合成音频") seed_button.click(generate_seed, inputs=[], outputs=seed) generate_button.click(generate_audio, inputs=[tts_text, mode_checkbox_group, sft_dropdown, prompt_text, prompt_wav_upload, prompt_wav_record, instruct_text, seed], outputs=[audio_output]) mode_checkbox_group.change(fn=change_instruction, inputs=[mode_checkbox_group], outputs=[instruction_text]) demo.queue(max_size=4, default_concurrency_limit=2) demo.launch(server_port=args.port) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--port', type=int, default=8000) parser.add_argument('--model_dir', type=str, default='speech_tts/CosyVoice-300M', help='local path or modelscope repo id') args = parser.parse_args() cosyvoice = CosyVoice(args.model_dir) sft_spk = cosyvoice.list_avaliable_spks() prompt_sr, target_sr = 16000, 22050 default_data = np.zeros(target_sr) main()