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import os
import wikipedia
os.system("pip install git+https://github.com/openai/whisper.git")
import gradio as gr
import whisper
import jiwer
from share_btn import community_icon_html, loading_icon_html, share_js
model = whisper.load_model("small")
wikipedia.set_lang("en")
def set_default_passage():
sum = wikipedia.summary("pirate code", sentences=2)
passage.value=sum
return sum
def update_passage(passage_name):
try:
sum = wikipedia.summary(wikipedia.search(passage_name)[0], sentences=2, auto_suggest=False)
print(sum, wikipedia.search(passage_name))
passage.value = sum
except:
sum = "Please specify your article theme differently"
return sum, "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
def inference(audio):
audio = whisper.load_audio(audio)
audio_length = audio.shape[-1]/16000
audio = whisper.pad_or_trim(audio)
mel = whisper.log_mel_spectrogram(audio).to(model.device)
_, probs = model.detect_language(mel)
options = whisper.DecodingOptions(fp16 = False)
result = whisper.decode(model, mel, options)
transformation = jiwer.Compose([
jiwer.ToLowerCase(),
jiwer.RemovePunctuation(),
jiwer.RemoveWhiteSpace(replace_by_space=True),
jiwer.RemoveMultipleSpaces(),
jiwer.ReduceToListOfListOfWords(word_delimiter=" ")
])
error = jiwer.wer(
passage.value,
result.text,
truth_transform=transformation,
hypothesis_transform=transformation
)
# error = jiwer.wer(passage, result.text)
we_num = error * len(passage.value.split())
# print(f"WER is {we_num}")
print(result.text)
print(passage.value)
return f"For a {audio_length} second audio, {we_num} errors were made, resulting in a final time of {audio_length + we_num}.\n\n{result.text}", gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
css = """
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: white;
border-color: black;
background: black;
}
input[type='range'] {
accent-color: black;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
max-width: 730px;
margin: auto;
padding-top: 1.5rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.prompt h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
#share-btn-container {
display: flex; margin-top: 1.5rem !important; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
}
#share-btn {
all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;
}
#share-btn * {
all: unset;
}
"""
block = gr.Blocks(css=css)
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<svg
width="0.65em"
height="0.65em"
viewBox="0 0 115 115"
fill="none"
xmlns="http://www.w3.org/2000/svg"
>
<rect width="23" height="23" fill="white"></rect>
<rect y="69" width="23" height="23" fill="white"></rect>
<rect x="23" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="46" width="23" height="23" fill="white"></rect>
<rect x="46" y="69" width="23" height="23" fill="white"></rect>
<rect x="69" width="23" height="23" fill="black"></rect>
<rect x="69" y="69" width="23" height="23" fill="black"></rect>
<rect x="92" width="23" height="23" fill="#D9D9D9"></rect>
<rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="115" y="46" width="23" height="23" fill="white"></rect>
<rect x="115" y="115" width="23" height="23" fill="white"></rect>
<rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect>
<rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="92" y="69" width="23" height="23" fill="white"></rect>
<rect x="69" y="46" width="23" height="23" fill="white"></rect>
<rect x="69" y="115" width="23" height="23" fill="white"></rect>
<rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect>
<rect x="46" y="46" width="23" height="23" fill="black"></rect>
<rect x="46" y="115" width="23" height="23" fill="black"></rect>
<rect x="46" y="69" width="23" height="23" fill="black"></rect>
<rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect>
<rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect>
<rect x="23" y="69" width="23" height="23" fill="black"></rect>
</svg>
<h1 style="font-weight: 900; margin-bottom: 7px;">
The Rap God Test
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
The point of the game is to say the given text as fast as possible without errors. Each error adds a one second penalty to the final time and is measured by the WER metric multiplied by text length. Once you mastered the pirate code example (my PB is 15.4), challenge your friends with another article of your choice !
The STT is powered by Whisper, a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. This demo cuts audio after around 30 secs.
</p>
</div>
"""
)
with gr.Group():
passage = gr.Textbox(value=set_default_passage, show_label=False)
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
audio = gr.Audio(
label="Input Audio",
show_label=False,
source="microphone",
type="filepath"
)
btn = gr.Button("Transcribe")
text = gr.Textbox(show_label=False, elem_id="result-textarea")
with gr.Row().style(mobile_collapse=False, equal_height=True):
passage_name = gr.Textbox(label="Challenge your friends with another Wikipedia article theme:", placeholder="The pirate code")
btn2 = gr.Button("Fetch another article")
with gr.Group(elem_id="share-btn-container"):
community_icon = gr.HTML(community_icon_html, visible=False)
loading_icon = gr.HTML(loading_icon_html, visible=False)
share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
btn.click(inference, inputs=[audio], outputs=[text, community_icon, loading_icon, share_button])
btn2.click(update_passage, inputs=[passage_name], outputs=[passage, text, community_icon, loading_icon, share_button])
share_button.click(None, [], [], _js=share_js)
gr.HTML('''
<div class="footer">
<p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - Gradio Demo by Manu
</p>
</div>
''')
block.launch()