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# Import necessary libraries
import gradio as gr
import numpy as np
# Define the function to transcribe audio
def transcribe(audio):
sr, y = audio
# Convert to mono if stereo
if y.ndim > 1:
y = y.mean(axis=1)
y = y.astype(np.float32)
y /= np.max(np.abs(y))
# Placeholder for the actual transcription logic
return "Transcribed text: " + " ".join([str(i) for i in y[:10]])
# Create a Gradio interface for full-context ASR
demo_full_context = gr.Interface(
transcribe,
gr.Audio(sources="microphone"),
"text",
)
# Define the function to transcribe streaming audio
def transcribe_stream(stream, new_chunk):
sr, y = new_chunk
# Convert to mono if stereo
if y.ndim > 1:
y = y.mean(axis=1)
y = y.astype(np.float32)
y /= np.max(np.abs(y))
if stream is not None:
stream = np.concatenate([stream, y])
else:
stream = y
# Placeholder for the actual transcription logic
return stream, "Transcribed text: " + " ".join([str(i) for i in stream[:10]])
# Create a Gradio interface for streaming ASR
demo_streaming = gr.Interface(
transcribe_stream,
["state", gr.Audio(sources=["microphone"], streaming=True)],
["state", "text"],
live=True,
)
# Launch the interfaces
if __name__ == "__main__":
demo_full_context.launch(show_error=True)
demo_streaming.launch()