Delete speech_to_text.py

speech_to_text.py

@@ -1,76 +0,0 @@
-from dotenv import load_dotenv
-import os
-from vosk import Model, KaldiRecognizer
-import pyaudio
-import json
-
-# Load environment variables from .env file
-load_dotenv()
-
-# Get the Vosk model path from the environment variable
-vosk_model_path = os.getenv("vosk_model_path")
-
-if not vosk_model_path:
-    print("Error: vosk_model_path is not set in the .env file.")
-    exit()
-
-# Initialize the Vosk model
-try:
-    model = Model(vosk_model_path)
-    print("Vosk model loaded successfully.")
-except Exception as e:
-    print(f"Failed to load Vosk model: {e}")
-    exit()
-
-# Initialize recognizer and audio input
-recognizer = KaldiRecognizer(model, 16000)
-audio = pyaudio.PyAudio()
-
-# Open audio stream
-stream = audio.open(format=pyaudio.paInt16, 
-                    channels=1, 
-                    rate=16000, 
-                    input=True, 
-                    frames_per_buffer=4000)
-stream.start_stream()
-
-print("Say 'start listening' to begin transcription and 'stop listening' to stop.")
-
-# State management
-is_listening = False
-
-try:
-    while True:
-        data = stream.read(4000, exception_on_overflow=False)
-
-        if recognizer.AcceptWaveform(data):
-            result = recognizer.Result()
-            text = json.loads(result)["text"]
-            
-            # Check for commands to start or stop listening
-            if "start listening" in text.lower():
-                is_listening = True
-                print("Listening started. Speak into the microphone.")
-                continue
-            elif "stop listening" in text.lower():
-                is_listening = False
-                print("Listening stopped. Say 'start listening' to resume.")
-                continue
-
-            # Transcribe if actively listening
-            if is_listening:
-                print(f"Transcription: {text}")
-        else:
-            # Handle partial results if needed
-            chunk_result = recognizer.PartialResult()
-            chunk_text = json.loads(chunk_result)["partial"]
-
-            # Display partial transcription only if actively listening
-            if is_listening and chunk_text:
-                print(f"chunk: {chunk_text}", end="\r")
-
-except KeyboardInterrupt:
-    print("\nExiting...")
-    stream.stop_stream()
-    stream.close()
-    audio.terminate()