audio update

.gitignore

@@ -133,4 +133,6 @@ EngToSpanishckpts/
 cmn.txt
 re-model.h5
 TestTranslationChinese/cmn.txt
-TestTranslationChinese/re-model.h5
+TestTranslationChinese/re-model.h5
+AudioToText/AudioToTextCKPT.hdf5
+AudioToTextCKPT.hdf5

AudioToText/condensedmodel.py

@@ -184,10 +184,11 @@ def getSpectro(wav_file):
 
     return spectrogram
 
+# Load Weights
+loadWeights()
 # CONVERT AUDIO TO TEXT
 def AudioToTextUsingModel(wav_file):
-    # Load Weights
-    loadWeights()
+
     
     # Get Spectrogram
     spectro = getSpectro(wav_file)

app.py

@@ -1,31 +1,47 @@
 # have to run this locally as streamlit run app.py
 import streamlit as st
 from Autocorrect.autocorrectreal import edit
-from TestTranslation.translation import *
+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("Translation model test")
 
-option = st.selectbox("Select input type:", ("text input", "audio input"))
+option = st.selectbox("Select input type:", ("Text input", "Audio input"))
 option2 = st.selectbox("Select translation language:", ("Spanish", "Chinese"))
-if option == "text input":
+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":
-            edited = edit(input_sentence)
-            st.write("Autocorrected sentence: " + edited)
             translated = decode_sequence(edited)[8:-5]
             st.write(translated)
             input_sentence = None
         else:
-            edited = edit(input_sentence)
-            st.write("Autocorrected sentence: " + edited)
             translated = decode_sequence_chinese(edited)[8:]
             st.write(translated)
             input_sentence = None
 else:
-    wav_sentence = st.file_uploader("Upload a wav file:")
-    st.button("Submit wav file")
-
+    wav_sentence = st.file_uploader("Upload a .wav file:")
+    option3 = st.selectbox("Select audio to text model to use:", ("Our pretrained model", "Google API"))
+    if st.button("Submit .wav 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