Create app.py

app.py

@@ -0,0 +1,43 @@
+mport 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")
+uploaded_file = st.file_uploader("Select an audio file",type=["mp3","mp4"])
+
+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()