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import gradio as gr
import time
from transformers import pipeline
import torch
import ffmpeg # Make sure it's ffmpeg-python
def main():
# Check if GPU is available
use_gpu = torch.cuda.is_available()
# Configure the pipeline to use the GPU if available
if use_gpu:
p = pipeline(
"automatic-speech-recognition",
model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h",
device=0
)
else:
p = pipeline(
"automatic-speech-recognition",
model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h"
)
def extract_audio_from_m3u8(url):
try:
output_file = "output_audio.aac"
ffmpeg.input(url).output(output_file).run(overwrite_output=True)
return output_file
except Exception as e:
return f"An error occurred: {e}"
def transcribe_function(audio, state, uploaded_audio, m3u8_url):
if m3u8_url:
audio = extract_audio_from_m3u8(m3u8_url)
if uploaded_audio is not None:
audio = uploaded_audio
if not audio:
# Return a meaningful message; no audio found
return {state_var: state, transcription_var: state}
try:
time.sleep(3)
text = p(audio, chunk_length_s=50)["text"]
state += text + "\n"
return {state_var: state, transcription_var: state}
except Exception as e:
return {
transcription_var: "An error occurred during transcription.",
state_var: state
}
def reset_output(transcription, state):
"""Function to reset the state to an empty string."""
return "", ""
with gr.Blocks() as demo:
state_var = gr.State("")
with gr.Row():
with gr.Column():
microphone = gr.Audio(
source="microphone",
type="filepath",
label="Microphone"
)
uploaded_audio = gr.Audio(
label="Upload Audio File",
type="filepath",
source="upload"
)
m3u8_url = gr.Textbox(
label="m3u8 URL | E.g.: from kvf.fo or logting.fo"
)
with gr.Column():
transcription_var = gr.Textbox(
type="text",
label="Transcription",
readonly=True
)
with gr.Row():
transcribe_button = gr.Button("Transcribe")
reset_button = gr.Button("Reset output")
transcribe_button.click(
transcribe_function,
[microphone, state_var, uploaded_audio, m3u8_url],
[transcription_var, state_var]
)
reset_button.click(
reset_output,
[transcription_var, state_var],
[transcription_var, state_var]
)
# Launch with the latest Gradio features
demo.launch()
if __name__ == "__main__":
main()
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