Create app.py

app.py

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+import streamlit as st
+import speech_recognition as sr
+import pyaudio
+import threading
+import queue
+
+FORMAT = pyaudio.paInt16
+CHANNELS = 1
+RATE = 44100
+CHUNK = 1024
+
+audio_queue = queue.Queue()
+text_queue = queue.Queue()
+
+
+def recognize_worker():
+    recognizer = sr.Recognizer()
+    while True:
+        audio_data = audio_queue.get()
+        if audio_data is None:
+            break
+        try:
+            text = recognizer.recognize_google(audio_data)
+            text_queue.put(text)
+        except sr.UnknownValueError:
+            pass
+
+
+def audio_stream():
+    p = pyaudio.PyAudio()
+    stream = p.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK)
+
+    recognizer = sr.Recognizer()
+    while not stop_flag.is_set():
+        data = stream.read(CHUNK, exception_on_overflow=False)
+        if len(data) == 0:
+            break
+        audio_data = sr.AudioData(data, RATE, 2)
+        audio_queue.put(audio_data)
+
+    stream.stop_stream()
+    stream.close()
+    p.terminate()
+
+
+st.title('Real-time Speech to Text')
+
+stop_flag = threading.Event()
+
+if st.button('Start Recording'):
+    stop_flag.clear()
+    threading.Thread(target=audio_stream, daemon=True).start()
+    threading.Thread(target=recognize_worker, daemon=True).start()
+    st.write('Recording started...')
+
+if st.button('Stop Recording'):
+    stop_flag.set()
+    audio_queue.put(None)
+    st.write('Recording stopped.')
+
+st.text_area('Text:', value='', key='text_area')
+
+if not text_queue.empty():
+    st.session_state.text_area += text_queue.get() + '\n'