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import streamlit as st
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")
# Function to convert audio to text
@st.cache
def audio2txt(audioname):
pipe = pipeline("automatic-speech-recognition", model="avery0/pipeline1model2")
rst = pipe(audioname)
return rst['text']
# Function to translate text
@st.cache
def translation(txt):
pipe = pipeline("translation", model= "Helsinki-NLP/opus-mt-en-zh")
rst = pipe(txt)
return rst
# Main function
def main():
uploaded_file = st.file_uploader("Select an audio file", type=["mp3", "wav","m4a"])
if uploaded_file is not None:
audio_data = uploaded_file.read()
st.audio(audio_data, format='audio/mp3/m4a')
# Stage 1: Audio to Text
st.text('Processing audio2txt...')
txt = audio2txt(audio_data)
st.write(txt)
# Stage 2: Text to Translation
st.text('Generating a translation...')
txt2 = translation(txt)
st.write(txt2)
if __name__ == "__main__":
main() |