Update app.py

app.py

@@ -1,37 +1,43 @@
-import streamlit as st
-import pyaudio
 import speech_recognition as sr
-from textblob import TextBlob
 import matplotlib.pyplot as plt
-
-def sentiment_analysis(text):
-    blob = TextBlob(text)
-    sentiment_score = blob.sentiment.polarity
-    return sentiment_score
+import numpy as np
+import sounddevice as sd
+from textblob import TextBlob
 
 def record_audio():
+    duration = 5  # in seconds
+    sample_rate = 44100  # in Hz
+    channels = 1
+
+    recording = sd.rec(int(duration * sample_rate), samplerate=sample_rate, channels=channels)
+    sd.wait()
+
+    return np.squeeze(recording)
+
+def transcribe_audio(audio):
     r = sr.Recognizer()
-    with sr.Microphone() as source:
-        st.write("Say something!")
-        audio = r.listen(source)
-        try:
-            text = r.recognize_google(audio)
-            sentiment_score = sentiment_analysis(text)
-            st.write("Transcription: ", text)
-            st.write("Sentiment Score: ", sentiment_score)
-            fig, ax = plt.subplots()
-            ax.bar(["Sentiment"], [sentiment_score])
-            st.pyplot(fig)
-        except sr.UnknownValueError:
-            st.write("Could not understand audio")
-        except sr.RequestError as e:
-            st.write("Could not request results from Google Speech Recognition service; {0}".format(e))
+    with sr.AudioFile(audio) as source:
+        audio_data = r.record(source)
+
+    return r.recognize_google(audio_data)
+
+def get_sentiment(text):
+    blob = TextBlob(text)
+    sentiment = blob.sentiment.polarity
+
+    return sentiment
+
+def plot_sentiment(sentiment):
+    plt.plot(sentiment)
+    plt.xlabel("Time (s)")
+    plt.ylabel("Sentiment")
+    plt.show()
 
 def main():
-    st.title("Speech to Sentiment Analysis")
-    st.write("Press 'Record' to start recording audio.")
-    if st.button("Record"):
-        record_audio()
+    audio = record_audio()
+    text = transcribe_audio(audio)
+    sentiment = [get_sentiment(sentence) for sentence in text.split('.')]
+    plot_sentiment(sentiment)
 
 if __name__ == "__main__":
     main()