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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.") | |