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# have to run this locally as streamlit run app.py
import streamlit as st
from Autocorrect.autocorrectreal import edit
from TestTranslation.translation import decode_sequence
from TestTranslationChinese.translation_model import decode_sequence_chinese
from AudioToText.condensedmodel import AudioToTextUsingAPI
from AudioToText.condensedmodel import AudioToTextUsingModel
st.title("FIRE COML Summer 2022 Translation Model")
option = st.selectbox("Select input type:", ("Text input", "Audio input"))
option2 = st.selectbox("Select translation language:", ("Spanish", "Chinese"))
if option == "Text input":
input_sentence = st.text_input("Enter input sentence:")
if input_sentence is not None and len(input_sentence) > 0:
edited = edit(input_sentence)
st.write("Autocorrected sentence: " + edited)
if option2 == "Spanish":
translated = decode_sequence(edited)[8:-5]
st.write(translated)
input_sentence = None
else:
translated = decode_sequence_chinese(edited)[8:]
st.write(translated)
input_sentence = None
else:
wav_sentence = st.file_uploader("Upload an audio file (.wav):", type=\
["wav"])
option3 = st.selectbox("Select audio to text model to use:", ("Our pretrained model", "Google API"))
if st.button("Submit audio file"):
if option3 == "Our pretrained model":
input_list = AudioToTextUsingModel(wav_sentence)
input_sentence = "".join(input_list)
else:
input_sentence = AudioToTextUsingAPI(wav_sentence)
st.write("Raw audio to text: " + input_sentence)
edited = edit(input_sentence)
st.write("Autocorrected sentence: " + edited)
if option2 == "Spanish":
translated = decode_sequence(edited)[8:-5]
st.write(translated)
input_sentence = None
else:
translated = decode_sequence_chinese(edited)[8:]
st.write(translated)
input_sentence = None
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