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import gradio as gr
import asr
# from tts import synthesize
mms_transcribe = gr.Interface(
fn=asr.transcribe,
inputs=[
gr.Audio(),
gr.Dropdown(
choices=[model for model in asr.models_info] + ["Compare All Models"],
label="Select Model for ASR",
value="ixxan/wav2vec2-large-mms-1b-uyghur-latin",
interactive=True
)
],
outputs="text",
#examples=ASR_EXAMPLES,
title="Speech-to-text",
description=(
"Transcribe audio from a microphone or input file."
),
#article=ASR_NOTE,
allow_flagging="never",
)
# mms_synthesize = gr.Interface(
# fn=synthesize,
# inputs=[
# gr.Text(label="Input text"),
# ],
# 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 from input text."),
# allow_flagging="never",
# )
tabbed_interface = gr.TabbedInterface(
[mms_transcribe],
["Speech-to-text"],
)
# tabbed_interface = gr.TabbedInterface(
# [mms_transcribe, mms_synthesize],
# ["Speech-to-text", "Text-to-speech"],
# )
with gr.Blocks() as demo:
tabbed_interface.render()
if __name__ == "__main__":
demo.queue()
demo.launch() |