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| # Copyright (c) Microsoft | |
| # 2022 Chengdong Liang ([email protected]) | |
| # | |
| # 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 gradio as gr | |
| import wesep | |
| import soundfile | |
| import torchaudio | |
| import os | |
| from scipy.signal import resample | |
| input_path = "./audios" | |
| output_path = "./extracted" | |
| if not os.path.exists(input_path): | |
| os.mkdir(input_path) | |
| if not os.path.exists(output_path): | |
| os.mkdir(output_path) | |
| en_model = wesep.load_model("english") | |
| def save_to_file(audio,filename,target_sr=16000): | |
| audio_path = os.path.join(input_path,filename) | |
| soundfile.write(audio_path,audio[1],audio[0]) | |
| pcm, sample_rate = torchaudio.load(audio_path) | |
| transform = torchaudio.transforms.Resample( | |
| orig_freq=audio[0], | |
| new_freq=target_sr) | |
| pcm = transform(pcm) | |
| torchaudio.save(audio_path, pcm, target_sr) | |
| return audio_path | |
| def speaker_extraction(audio1, audio2, mixture, select_speaker='#1'): | |
| if audio1 == None or audio2 == None or mixture == None: | |
| print("??") | |
| return gr.Warning("The audio file cannot be empty, please upload a valid audio file. 音频文件不能为空，请上传有效的音频文件。") | |
| audio_path1 = save_to_file(audio1,"enroll_1.wav",16000) | |
| audio_path2 = save_to_file(audio2,"enroll_2.wav",16000) | |
| audio_mixture = save_to_file(mixture,"mixture.wav",16000) | |
| model = en_model | |
| if select_speaker == '#1': | |
| select_speaker = audio_path1 | |
| elif select_speaker == '#2': | |
| select_speaker = audio_path2 | |
| speech = model.extract_speech(audio_mixture,select_speaker) | |
| audio_speech = output_path + "/speech.wav" | |
| soundfile.write(audio_speech,speech[0],16000) | |
| return audio_speech | |
| inputs = [ | |
| gr.Audio( | |
| show_download_button = True, | |
| label='Enroll Speaker#1', | |
| ), | |
| gr.Audio( | |
| show_download_button = True, | |
| label='Enroll Speaker#2'), | |
| gr.Audio( | |
| show_download_button = True, | |
| label='Mixture'), | |
| gr.Radio(['#1', '#2'], label='Extract Speaker #'), | |
| ] | |
| output = gr.Audio(type="filepath",label="Extract Speaker") | |
| # description | |
| description = ("<p>WeSep Demo ! Try it with your own voice ! Note: We recommend that the audio length be greater than 5s !</p>") | |
| article = ( | |
| "<p style='text-align: center'>" | |
| "<a href='https://github.com/wenet-e2e/wesep' target='_blank'>Github: Learn more about WeSep</a>" | |
| "</p>") | |
| examples = [ | |
| ['examples/enroll_1.wav', 'examples/enroll_2.wav', 'examples/mixture.wav','#1'], | |
| ['examples/enroll1_zh.wav', 'examples/enroll2_zh.wav', 'examples/mixture_zh.wav','#2'], | |
| ] | |
| interface = gr.Interface( | |
| fn=speaker_extraction, | |
| inputs=inputs, | |
| outputs=output, | |
| title="Speaker Extraction in WeSep : 基于 WeSep 的说话人提取", | |
| description=description, | |
| article=article, | |
| examples=examples | |
| ) | |
| interface.launch() | |