Update app files

neural_acoustic_distance.py

@@ -1,3 +1,4 @@
+from unicodedata import name
 import streamlit as st
 import pandas as pd
 import numpy as np
@@ -102,6 +103,11 @@ def compute_costs(gcm):
     res = [np.mean(x) for x in res]
     return res, n
 
+def play_audio(filename):
+    audio_file = open(filename, "rb")
+    audio_bytes = audio_file.read()
+    st.audio(audio_bytes, format="audio/wav")
+
 st.subheader("Audio file selection:")
 
 filename_x = st.selectbox(
@@ -110,8 +116,10 @@ filename_x = st.selectbox(
 
 if filename_x == "falling_huud_mobiel_201145.wav":
     filename_x = "./examples/falling_huud_mobiel_201145.wav"
+    play_audio(filename_x)
 if filename_x == "falling_hood_mobiel_203936.wav":
     filename_x = "./examples/falling_hood_mobiel_203936.wav"
+    play_audio(filename_x)
 
 filename_y = st.selectbox(
 "Filename (y-axis):",
@@ -119,13 +127,15 @@ filename_y = st.selectbox(
 
 if filename_y == "falling_huud_mobiel_201145.wav":
     filename_y = "./examples/falling_huud_mobiel_201145.wav"
+    play_audio(filename_y)
 if filename_y == "falling_hood_mobiel_203936.wav":
     filename_y = "./examples/falling_hood_mobiel_203936.wav"
+    play_audio(filename_y)
 
 if filename_x == "custom upload":
-    filename_x = st.file_uploader("Choose a file", key = "f_x")
+    filename_x = st.file_uploader("Choose a file (x-axis)", key = "f_x")
 if filename_y == "custom upload":
-    filename_y = st.file_uploader("Choose a file", key = "f_y")
+    filename_y = st.file_uploader("Choose a file (y-axis)", key = "f_y")
 
 if filename_x is not None and filename_y is not None and featurizer_a is not None:
     print(f"\nX: {filename_x}\nY: {filename_y}")