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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 | |
mms_transcribe = gr.Interface( | |
fn=transcribe, | |
inputs=[ | |
gr.Audio(), | |
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_identify = gr.Interface( | |
fn=identify, | |
inputs=[ | |
gr.Audio(), | |
], | |
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</p>" | |
) | |
gr.HTML( | |
"""<center>Text-to-Speech, Speech-to-Text, and Language Recognition for 1,100+ languages.</center>""" | |
) | |
tabbed_interface.render() | |
if __name__ == "__main__": | |
demo.queue() | |
demo.launch() |