recognize_sphinx()

recognize_sphinx(
    audio_data: AudioData,
    language: str | tuple = "en-US",
    keyword_entries: list[tuple[str, float]] | None = None,
    grammar: str | None = None,
    show_all: bool = False
) -> str | object

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 Sphinx (offline)
try:
    text = r.recognize_sphinx(audio)
    print(f"You said: {text}")
except sr.UnknownValueError:
    print("Could not understand audio")
except sr.RequestError as e:
    print(f"Sphinx error: {e}")

import speech_recognition as sr

r = sr.Recognizer()

# Define keywords to listen for
keywords = [
    ("turn on", 0.7),
    ("turn off", 0.7),
    ("lights", 0.8),
    ("music", 0.8),
    ("stop", 0.9)
]

with sr.Microphone() as source:
    print("Listening for commands...")
    audio = r.listen(source)

try:
    # Only recognize specified keywords
    text = r.recognize_sphinx(audio, keyword_entries=keywords)
    print(f"Detected command: {text}")
    
    # Process command
    if "turn on" in text.lower() and "lights" in text.lower():
        print("Turning on the lights...")
    elif "turn off" in text.lower() and "lights" in text.lower():
        print("Turning off the lights...")
except sr.UnknownValueError:
    print("No keyword detected")

import speech_recognition as sr

r = sr.Recognizer()

# Create JSGF grammar file (grammar.jsgf)
# #JSGF V1.0;
# grammar commands;
# public <commands> = turn on lights | turn off lights | play music | stop music;

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

try:
    # Constrain recognition to grammar
    text = r.recognize_sphinx(audio, grammar="grammar.jsgf")
    print(f"Command: {text}")
except sr.UnknownValueError:
    print("Command not recognized")

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_sphinx(audio)
    print(f"Transcript: {text}")
except sr.RequestError as e:
    print(f"Error: {e}")

import speech_recognition as sr

r = sr.Recognizer()

# Custom Sphinx model paths
custom_model = (
    "/path/to/acoustic-model",
    "/path/to/language-model.lm.bin",
    "/path/to/dictionary.dict"
)

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

try:
    text = r.recognize_sphinx(audio, language=custom_model)
    print(f"Transcript: {text}")
except sr.RequestError as e:
    print(f"Error: {e}")

import speech_recognition as sr

r = sr.Recognizer()

# Wake word detection
wake_words = [("hey assistant", 0.6)]

print("Listening for wake word...")
with sr.Microphone() as source:
    while True:
        audio = r.listen(source)
        
        try:
            # Listen for wake word
            text = r.recognize_sphinx(audio, keyword_entries=wake_words)
            if "hey assistant" in text.lower():
                print("Wake word detected! Listening for command...")
                
                # Now listen for actual command
                audio = r.listen(source)
                command = r.recognize_sphinx(audio)
                print(f"Command: {command}")
                # Process command...
        except sr.UnknownValueError:
            pass  # No wake word, keep listening

pip install pocketsphinx

keywords = [
    ("critical alert", 0.9),  # Very sensitive - don't miss this
    ("hello", 0.5),          # Balanced
    ("background noise", 0.2) # Very insensitive
]

#JSGF V1.0;

grammar commands;

public <command> = <action> <object>;
<action> = turn on | turn off | play | stop;
<object> = lights | music | television;

text = r.recognize_sphinx(audio, grammar="commands.jsgf")