Update app.py

app.py

@@ -1,50 +1,37 @@
 import streamlit as st
-from pocketsphinx import LiveSpeech, get_model_path
-import os
-import sounddevice as sd
-import numpy as np
-import scipy.io.wavfile as wav
-
-# Function to capture audio from the mic
-def record_audio(filename='temp.wav', duration=5, fs=16000):
-    st.text("Recording Audio...")
-    with st.spinner(f'Recording for {duration} seconds...'):
-        myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=1)
-        sd.wait()  # Waits until recording is finished
-        wav.write(filename, fs, myrecording)  # Save as WAV file 
-
-# Get the model path for pocketsphinx
-model_path = get_model_path()
-config = {
-    'verbose': False,
-    'hmm': os.path.join(model_path, 'en-us'),
-    'lm': os.path.join(model_path, 'en-us.lm.bin'),
-    'dict': os.path.join(model_path, 'cmudict-en-us.dict')
-}
-
-# Streamlit UI
-st.title("Simple Speech Recognition with Streamlit and PocketSphinx")
-button = st.button("Press to Speak")
-
-# Store the state of the recording
-if 'recording_done' not in st.session_state:
-    st.session_state.recording_done = False
-
-# When the button is pressed
-if button:
-    # Record the audio
-    record_audio()
-    st.session_state.recording_done = True
-
-# If an audio was recorded, process it with PocketSphinx
-if st.session_state.recording_done:
-    audio = LiveSpeech(**config)
-
-    st.text("Processing Audio...")
-    with st.spinner('Recognizing...'):
-        for phrase in audio:
-            st.write(phrase)
-            break  # We'll stop after the first phrase
-
-    # Reset the state
-    st.session_state.recording_done = False
+from bokeh.models.widgets import Button
+from bokeh.models import CustomJS
+from streamlit_bokeh_events import streamlit_bokeh_events
+
+stt_button = Button(label="Speak", width=100)
+
+stt_button.js_on_event("button_click", CustomJS(code="""
+    var recognition = new webkitSpeechRecognition();
+    recognition.continuous = true;
+    recognition.interimResults = true;
+ 
+    recognition.onresult = function (e) {
+        var value = "";
+        for (var i = e.resultIndex; i < e.results.length; ++i) {
+            if (e.results[i].isFinal) {
+                value += e.results[i][0].transcript;
+            }
+        }
+        if ( value != "") {
+            document.dispatchEvent(new CustomEvent("GET_TEXT", {detail: value}));
+        }
+    }
+    recognition.start();
+    """))
+
+result = streamlit_bokeh_events(
+    stt_button,
+    events="GET_TEXT",
+    key="listen",
+    refresh_on_update=False,
+    override_height=75,
+    debounce_time=0)
+
+if result:
+    if "GET_TEXT" in result:
+        st.write(result.get("GET_TEXT"))