Spaces:
Running
Running
File size: 1,155 Bytes
40cc2a1 fdcc446 d531300 fdcc446 d531300 2256efc d531300 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 |
import streamlit as st
import gradio as gr
from transformers import pipeline
st.set_page_config(page_title="Your English audio to Chinese text", page_icon="🦜")
st.header("Turn Your English Audio to Chinese text")
uploaded_file = st.file_uploader("Select an audio file")
if uploaded_file is not None:
print(uploaded_file)
bytes_data = uploaded_file.getvalue()
with open(uploaded_file.name, "wb") as file:
file.write(bytes_data)
st.image(uploaded_file, caption="Uploaded Audio",
use_column_width=True)
# function part
def audio2txt(audioname):
pipe = pipeline("Automatic-Speech-Recognition", model="avery0/pipeline1model2")
rst = pipe(audioname)
return rst
def translation(txt):
pipe = pipeline(model="translation", model="DDDSSS/translation_en-zh")
rst = pipe(txt)
return rst
def main():
#Stage 1: Aido to Text
st.text('Processing audio2txt...')
txt = audio2txt(uploaded_file.name)
st.write(txt)
#Stage 2: Text to Story
st.text('Generating a translation...')
txt2 = translation(txt)
st.write(txt2)
# main part
if __name__ == "__main__":
main() |