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Running
on
A10G
import gradio as gr | |
import librosa | |
from asr import transcribe, ASR_EXAMPLES, ASR_LANGUAGES, ASR_NOTE | |
from tts import synthesize, TTS_EXAMPLES, TTS_LANGUAGES | |
from lid import identify, LID_EXAMPLES | |
demo = gr.Blocks() | |
mms_select_source_trans = gr.Radio( | |
["Record from Mic", "Upload audio"], | |
label="Audio input", | |
value="Record from Mic", | |
) | |
mms_mic_source_trans = gr.Audio(source="microphone", type="filepath", label="Use mic") | |
mms_upload_source_trans = gr.Audio( | |
source="upload", type="filepath", label="Upload file", visible=False | |
) | |
mms_transcribe = gr.Interface( | |
fn=transcribe, | |
inputs=[ | |
mms_select_source_trans, | |
mms_mic_source_trans, | |
mms_upload_source_trans, | |
gr.Dropdown( | |
[f"{k} ({v})" for k, v in ASR_LANGUAGES.items()], | |
label="Language", | |
value="eng English", | |
), | |
# gr.Checkbox(label="Use Language Model (if available)", default=True), | |
], | |
outputs="text", | |
examples=ASR_EXAMPLES, | |
title="Speech-to-text", | |
description=( | |
"Transcribe audio from a microphone or input file in your desired language." | |
), | |
article=ASR_NOTE, | |
allow_flagging="never", | |
) | |
mms_synthesize = gr.Interface( | |
fn=synthesize, | |
inputs=[ | |
gr.Text(label="Input text"), | |
gr.Dropdown( | |
[f"{k} ({v})" for k, v in TTS_LANGUAGES.items()], | |
label="Language", | |
value="eng English", | |
), | |
gr.Slider(minimum=0.1, maximum=4.0, value=1.0, step=0.1, label="Speed"), | |
], | |
outputs=[ | |
gr.Audio(label="Generated Audio", type="numpy"), | |
gr.Text(label="Filtered text after removing OOVs"), | |
], | |
examples=TTS_EXAMPLES, | |
title="Text-to-speech", | |
description=("Generate audio in your desired language from input text."), | |
allow_flagging="never", | |
) | |
mms_select_source_iden = gr.Radio( | |
["Record from Mic", "Upload audio"], | |
label="Audio input", | |
value="Record from Mic", | |
) | |
mms_mic_source_iden = gr.Audio(source="microphone", type="filepath", label="Use mic") | |
mms_upload_source_iden = gr.Audio( | |
source="upload", type="filepath", label="Upload file", visible=False | |
) | |
mms_identify = gr.Interface( | |
fn=identify, | |
inputs=[ | |
mms_select_source_iden, | |
mms_mic_source_iden, | |
mms_upload_source_iden, | |
], | |
outputs=gr.Label(num_top_classes=10), | |
examples=LID_EXAMPLES, | |
title="Language Identification", | |
description=("Identity the language of input audio."), | |
allow_flagging="never", | |
) | |
tabbed_interface = gr.TabbedInterface( | |
[mms_transcribe, mms_synthesize, mms_identify], | |
["Speech-to-text", "Text-to-speech", "Language Identification"], | |
) | |
with gr.Blocks() as demo: | |
gr.Markdown( | |
"<p align='center' style='font-size: 20px;'>MMS: Scaling Speech Technology to 1000+ languages demo. See our <a href='https://ai.facebook.com/blog/multilingual-model-speech-recognition/'>blog post</a> and <a href='https://arxiv.org/abs/2305.13516'>paper</a>.</p>" | |
) | |
gr.HTML( | |
"""<center>Click on the appropriate tab to explore Speech-to-text (ASR), Text-to-speech (TTS) and Language identification (LID) demos. </center>""" | |
) | |
gr.HTML( | |
"""<center><a href="https://huggingface.co/spaces/facebook/MMS?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for more control and no queue.</center>""" | |
) | |
tabbed_interface.render() | |
mms_select_source_trans.change( | |
lambda x: [ | |
gr.update(visible=True if x == "Record from Mic" else False), | |
gr.update(visible=True if x == "Upload audio" else False), | |
], | |
inputs=[mms_select_source_trans], | |
outputs=[mms_mic_source_trans, mms_upload_source_trans], | |
queue=False, | |
) | |
mms_select_source_iden.change( | |
lambda x: [ | |
gr.update(visible=True if x == "Record from Mic" else False), | |
gr.update(visible=True if x == "Upload audio" else False), | |
], | |
inputs=[mms_select_source_iden], | |
outputs=[mms_mic_source_iden, mms_upload_source_iden], | |
queue=False, | |
) | |
gr.HTML( | |
""" | |
<div class="footer" style="text-align:center"> | |
<p> | |
Model by <a href="https://ai.facebook.com" style="text-decoration: underline;" target="_blank">Meta AI</a> - Gradio Demo by π€ Hugging Face | |
</p> | |
</div> | |
""" | |
) | |
demo.queue(concurrency_count=10) | |
demo.launch() | |