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# Copyright (c) Microsoft
# 2022 Chengdong Liang (liangchengdong@mail.nwpu.edu.cn)
#
# 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()
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