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from funasr_onnx import Fsmn_vad, Paraformer, CT_Transformer
from transcribe import get_models, transcribe
import soundfile
import gradio as gr
import pytube as pt
import datetime
import os
asr_model, vad_model, punc_model = get_models("./models")
def convert_to_wav(in_filename: str) -> str:
"""Convert the input audio file to a wave file"""
out_filename = in_filename + ".wav"
if '.mp3' in in_filename:
_ = os.system(f"ffmpeg -y -i '{in_filename}' -acodec pcm_s16le -ac 1 -ar 16000 '{out_filename}'")
else:
_ = os.system(f"ffmpeg -hide_banner -y -i '{in_filename}' -ar 16000 '{out_filename}'")
speech, _ = soundfile.read(out_filename)
print(f"load speech shape {speech.shape}")
return speech
def file_transcribe(microphone, file_upload):
warn_output = ""
if (microphone is not None) and (file_upload is not None):
warn_output = (
"WARNING: You've uploaded an audio file and used the microphone. "
"The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
)
elif (microphone is None) and (file_upload is None):
return "ERROR: You have to either use the microphone or upload an audio file"
file = microphone if microphone is not None else file_upload
speech = convert_to_wav(file)
items = []
vad_model.vad_scorer.AllResetDetection()
for item in transcribe(speech, asr_model, vad_model, punc_model):
items.append(item)
print(item)
text = "\n".join(items)
return warn_output + text
def _return_yt_html_embed(yt_url):
video_id = yt_url.split("?v=")[-1]
HTML_str = (
f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
" </center>"
)
return HTML_str
def youtube_transcribe(yt_url):
yt = pt.YouTube(yt_url)
html_embed_str = _return_yt_html_embed(yt_url)
stream = yt.streams.filter(only_audio=True)[0]
filename = f"audio.mp3"
stream.download(filename=filename)
speech=convert_to_wav(filename)
items = []
vad_model.vad_scorer.AllResetDetection()
for item in transcribe(speech, asr_model, vad_model, punc_model):
items.append(item)
print(item)
text = "\n".join(items)
os.system(f"rm -rf audio.mp3 audio.mp3.wav")
return html_embed_str, text
def run():
gr.close_all()
demo = gr.Blocks()
mf_transcribe = gr.Interface(
fn=file_transcribe,
inputs=[
gr.inputs.Audio(source="microphone", type="filepath", optional=True),
gr.inputs.Audio(source="upload", type="filepath", optional=True),
],
outputs="text",
layout="horizontal",
theme="huggingface",
title="ParaformerX: Copilot for Audio",
description=(
"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the the pretrained paraformer model to transcribe audio files of arbitrary length."
),
allow_flagging="never",
)
yt_transcribe = gr.Interface(
fn=youtube_transcribe,
inputs=[gr.inputs.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")],
outputs=["html", "text"],
layout="horizontal",
theme="huggingface",
title="Demo: Transcribe YouTube",
description=(
"Transcribe long-form YouTube videos with the click of a button! Demo uses the the pretrained paraformer model to transcribe audio files of arbitrary length."
),
allow_flagging="never",
)
with demo:
gr.TabbedInterface([mf_transcribe, yt_transcribe], ["Transcribe Audio", "Transcribe YouTube"])
demo.launch(server_name="0.0.0.0", server_port=7860, enable_queue=True)
if __name__ == "__main__":
run() |