Update app.py

app.py

@@ -24,6 +24,7 @@ except Exception as e:
 # model_path = 'TrillsonFeature_model'
 # m = hub.load(model_path)
 m = hub.KerasLayer('https://tfhub.dev/google/nonsemantic-speech-benchmark/trillsson4/1')
+
 class TransformerEncoder(tf.keras.layers.Layer):
     def __init__(self, embed_dim, num_heads, ff_dim, rate=0.01, **kwargs):
         super(TransformerEncoder, self).__init__(**kwargs)
@@ -163,10 +164,11 @@ if option == "Upload an audio file":
         start_time = time.time()  # Record start time
         with st.spinner('Extracting features...'):
             # Process the uploaded file
-            with open("temp_audio.wav", "wb") as f:
+            temp_audio_path = os.path.join(".", "temp_audio.wav")
+            with open(temp_audio_path, "wb") as f:
                 f.write(uploaded_file.getbuffer())
-            features = extract_features("temp_audio.wav")
-            os.remove("temp_audio.wav")
+            features = extract_features(temp_audio_path)
+            os.remove(temp_audio_path)
             run_prediction(features)
         elapsed_time = round(time.time() - start_time, 2)
         st.write(f"Elapsed Time: {elapsed_time} seconds")
@@ -271,7 +273,7 @@ else:  # Option is "Record audio"
                         const audioUrl = URL.createObjectURL(audioBlob);
                         const a = document.createElement('a');
                         a.href = audioUrl;
-                        a.download = './recorded_audio.wav';
+                        a.download = 'recorded_audio.wav';
                         document.body.appendChild(a);
                         a.click();