recognize_vosk()

recognize_vosk(
    audio_data: AudioData,
    verbose: bool = False
) -> str | dict

import speech_recognition as sr

# Initialize recognizer
r = sr.Recognizer()

# Record audio
with sr.Microphone() as source:
    print("Say something!")
    audio = r.listen(source)

# Recognize with Vosk (offline)
try:
    text = r.recognize_vosk(audio)
    print(f"You said: {text}")
except sr.SetupError as e:
    print(f"Setup error: {e}")

import speech_recognition as sr
import json

r = sr.Recognizer()

with sr.Microphone() as source:
    audio = r.listen(source)

try:
    # Get full result
    result = r.recognize_vosk(audio, verbose=True)
    print(json.dumps(result, indent=2))
    print(f"Transcript: {result['text']}")
except sr.SetupError as e:
    print(f"Error: {e}")

import speech_recognition as sr

r = sr.Recognizer()

# Load audio file
with sr.AudioFile("speech.wav") as source:
    audio = r.record(source)

try:
    text = r.recognize_vosk(audio)
    print(f"Transcript: {text}")
except sr.SetupError as e:
    print(f"Error: {e}")

import speech_recognition as sr

r = sr.Recognizer()

with sr.Microphone() as source:
    print("Speak continuously. Press Ctrl+C to stop.")
    r.adjust_for_ambient_noise(source)
    
    try:
        while True:
            audio = r.listen(source)
            try:
                text = r.recognize_vosk(audio)
                if text:  # Only print non-empty results
                    print(f"Recognized: {text}")
            except sr.SetupError as e:
                print(f"Error: {e}")
                break
    except KeyboardInterrupt:
        print("\nStopped.")

import speech_recognition as sr

r = sr.Recognizer()

def process_command(command):
    """Process voice commands"""
    command = command.lower()
    
    if "turn on" in command and "light" in command:
        print("Turning on the lights...")
    elif "turn off" in command and "light" in command:
        print("Turning off the lights...")
    elif "what time" in command:
        import datetime
        now = datetime.datetime.now()
        print(f"It's {now.strftime('%I:%M %p')}")
    elif "stop" in command or "exit" in command:
        return False
    else:
        print(f"Unknown command: {command}")
    return True

print("Voice assistant ready. Say 'stop' or 'exit' to quit.")

with sr.Microphone() as source:
    r.adjust_for_ambient_noise(source)
    
    while True:
        print("\nListening...")
        audio = r.listen(source)
        
        try:
            command = r.recognize_vosk(audio)
            if command:
                print(f"You said: {command}")
                if not process_command(command):
                    break
        except sr.SetupError as e:
            print(f"Error: {e}")
            break

import speech_recognition as sr
from pathlib import Path

r = sr.Recognizer()

# Process all WAV files in a directory
audio_dir = Path("recordings")

for audio_file in audio_dir.glob("*.wav"):
    print(f"\nProcessing: {audio_file.name}")
    
    with sr.AudioFile(str(audio_file)) as source:
        audio = r.record(source)
    
    try:
        text = r.recognize_vosk(audio)
        print(f"Transcript: {text}")
        
        # Save transcript
        transcript_file = audio_file.with_suffix(".txt")
        transcript_file.write_text(text)
    except sr.SetupError as e:
        print(f"Error: {e}")

pip install vosk

speech_recognition/models/vosk/

sprc download vosk

# Example directory structure
speech_recognition/
  models/
    vosk/
      am/         # Acoustic model
      conf/       # Configuration
      graph/      # Language model
      ivector/    # i-Vector extractor

import speech_recognition as sr

r = sr.Recognizer()

# This will raise SetupError if model is not found
try:
    with sr.Microphone() as source:
        audio = r.listen(source, timeout=1)
        text = r.recognize_vosk(audio)
    print("Vosk is ready!")
except sr.SetupError as e:
    print(f"Setup error: {e}")
    print("Please download the Vosk model.")

SetupError: Vosk model not found at /path/to/models/vosk.
Please download the model using `sprc download vosk` command.