Spaces:
Sleeping
Sleeping
File size: 5,837 Bytes
594893f 5e48419 594893f 5e48419 594893f 5e48419 a96b890 a12adfc 5e48419 594893f 5e48419 594893f 5e48419 a5fcb05 5e48419 594893f 5e48419 a12adfc 5e48419 594893f 5e48419 594893f 5e48419 594893f 5e48419 594893f 5e48419 594893f 5e48419 594893f 5e48419 594893f 5e48419 594893f 983b6c1 5e48419 983b6c1 5e48419 594893f 983b6c1 594893f 983b6c1 2ce6def 594893f 3b71270 594893f 5e48419 a12adfc 5e48419 a12adfc 5e48419 594893f a12adfc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 |
import gradio as gr
import re
import os
import requests
import time
import soundfile as sf
import io
def audio_to_bytes(audio):
data, sr = sf.read(audio)
audio_bytes = io.BytesIO()
sf.write(audio_bytes, data, sr, format='WAV')
audio_bytes.seek(0)
return audio_bytes
def langswitch_API_call(audio, language):
audio_bytes = audio_to_bytes(audio)
files = {'file': (f'audio_chunk.wav', audio_bytes, 'audio/wav')}
api_url = os.getenv("api_url")
response = requests.post(f"{api_url}/online/http?language={language}", files=files)
if response.status_code != 200:
print(response)
raise Exception("API error")
return response.json()
def transcribe_base(audio, language):
response = langswitch_API_call(audio, language)
print(response)
transcription = response["transcription"]
is_new_speaker = response["is_new_speaker"]
speaker = response["classified_speaker"]
if is_new_speaker:
speaker_class_string = f'New speaker detected. Assigned new ID {speaker}'
else:
speaker_class_string = f'Speaker found in database, ID {speaker}'
return transcription, speaker_class_string
def transcribe_mic(audio_microphone, language):
print("Transcription microphone")
return transcribe_base(audio_microphone, language)
def transcribe_file(audio_upload, language):
print("Transcription local file")
return transcribe_base(audio_upload, language)
css_content = """
/*
.gradio-container{
padding: 0 !important;
}
.html-container{
padding: 0 !important;
}
*/
#orai-info{
padding: 50px;
text-align: center;
font-size: 1rem;
background: url('https://elia.eus/static/elhuyar/img/landing_page/ig.webp') rgba(0,0,0,0.8);
background-repeat: no-repeat;
background-position: center center;
background-size: cover;
background-blend-mode: multiply;
}
#orai-info-text p{
color: white !important;
}
/*
#orai-info img{
margin: auto;
display: block;
margin-bottom: 1rem;
}*/
.bold{
font-weight: bold;
color: inherit !important;
}
footer{
display:none !important
}
.logos{
display: flex;
justify-content: center;
}
.sermas-logo{
display: flex;
align-items: center;
margin-right: 3rem;
}
.sermas-logo span{
color: white !important;
font-size: 2.5rem;
font-family: Verdana, Geneva, sans-serif !important;
font-weight: bold;
}
.text-elhuyar{
color: #0045e7;
}
#header{
padding: 50px;
padding-top: 30px;
background-color: #5b65a7;
}
#header h1,h3{
color: white;
}
button.primary{
background-color: #5b65a7;
}
button.primary:hover{
background-color: #3c4687;
}
button.selected{
color: #5b65a7 !important;
}
button.selected::after{
background-color: #5b65a7;
}
.record-button::before{
background: #5b65a7;
}
"""
demo = gr.Blocks(css=css_content) #, fill_width=True)
with demo:
gr.HTML("""
<div id="header">
<h1>LANGSWITCH</h1>
<h3>Multilingual Automatic Speech Recognition in noisy environments</h3>
</div>
""")
with gr.Tab("Transcribe microphone"):
iface = gr.Interface(
fn=transcribe_mic,
inputs=[
gr.Audio(sources="microphone", type="filepath"),
gr.Dropdown(choices=[("English", "en"),
("Spanish", "es"),
("French", "fr"),
("Italian", "it"),
("Basque", "eu")],
value="en")
],
outputs=[
gr.Textbox(label="Transcription", autoscroll=False),
gr.Textbox(label="Speaker Identification", autoscroll=False)
],
allow_flagging="never",
)
with gr.Tab("Transcribe local file"):
iface = gr.Interface(
fn=transcribe_file,
inputs=[
gr.Audio(sources="upload", type="filepath"),
gr.Dropdown(choices=[("English", "en"),
("Spanish", "es"),
("French", "fr"),
("Italian", "it"),
("Basque", "eu")],
value="en")
],
outputs=[
gr.Textbox(label="Transcription", autoscroll=False),
gr.Textbox(label="Speaker Identification", autoscroll=False)
],
allow_flagging="never",
)
gr.HTML("""
<div id="orai-info">
<div class="logos">
<div class="sermas-logo">
<img src="https://sermasproject.eu/wp-content/uploads/2023/04/sermas-logo.png" width=100/>
<span>SERMAS</span>
</div>
<img src="https://www.orai.eus/themes/custom/orai_for_drupal9/orai_bw.svg" width=175/>
</div>
<div id="orai-info-text">
<p>The <span class="bold">LANGSWITCH</span> sub-project is part of the Open Call 1 of the <span class="bold">SERMAS</span> project. The goal of the <span class="bold">SERMAS</span> project is to provide socially-acceptable extended reality models and systems.</p>
<p>The technology powering LANGSWITCH was developed by <span class="bold">Orai NLP Teknologiak</span></p>
<p><span class="bold">Orai NLP Teknologiak</span> specializes in research, development, and innovation in artificial intelligence, with a focus on fostering a more competitive industrial and business landscape, enhancing public administration efficiency, and promoting a more inclusive society.</p>
</div>
</div>
<p>""")
demo.queue(max_size=1)
demo.launch(share=False, max_threads=3, auth=(os.getenv("username"), os.getenv("password")), auth_message="Please provide a username and a password.")
|