Answers for "voice recognition python"

python speech recognition

#pip install SpeechRecognition
#in case of error use 'pip install pyaudio' or...
#in case of error use 'pip install pipwin' then 'pipwin install pyaudio'
#if error continued you may need to use python 3.6 or lower as the latest 
#python may not support pyaudio... 
import speech_recognition as sr
import pyttsx3

#audio of system to respond
engine = pyttsx3.init('sapi5')
voices = engine.getProperty('voices')
engine.setProperty('voice', voices[0].id)
engine.setProperty('rate',180)

def speak(audio):
    engine.say(audio)
    engine.runAndWait()

# simple function to recognise speech from user
def takecommand():
    #it takes microphone input and returns string output
    r = sr.Recognizer()
    with sr.Microphone() as source:
        print('Listening.....')
        r.pause_threshold = 1
        r.energy_threshold = 4000
        audio = r.listen(source)

    try:
        print('Recognising...')
        query = r.recognize_google(audio, language='en-in')
        print('User Said : ' , query)

    except Exception as e:
        print('exception : ',e)

        speak("Sorry, I didn't hear that, Say that again Please")
        return "None"
    return query
while True:
  query = takecommand() # whatever user says will be stored in this variable
  print("The Test got in program is : "+query)

text recognition python library

import cv2 
import pytesseract

img = cv2.imread('image.jpg')

# Adding custom options
custom_config = r'--oem 3 --psm 6'
pytesseract.image_to_string(img, config=custom_config)

python speech to text

import speech_recognition as sr


        def main():

            r = sr.Recognizer()

            with sr.Microphone() as source:
                r.adjust_for_ambient_noise(source)

                audio = r.listen(source)

                try:

                    print(r.recognize_google(audio))

                except Exception as e:
                    print("Error :  " + str(e))


                with open("recorded.wav", "wb") as f:
                    f.write(audio.get_wav_data())


        if __name__ == "__main__":
            main()

python speech recognition

import speech_recognition as sr

def take_command():
    r = sr.Recognizer()
    with sr.Microphone() as source:
        print('Listening...')
        r.pause_threshold = 1
        r.energy_threshold = 50
        audio = r.listen(source)

    try:
        print('Recognizing...')
        qry = r.recognize_google(audio, language='en-in')
        print(f"user said: {qry}n")
        
#     if any error occurs this line will run
    except Exeption as e:
    # if you don't want to print the error comment the bottom line
        print(e)
        print('Say that again pleasen')
        return 'None'

    return qry
  
if __name__ == '__main__':
	while True:
  		qry = takecommand().lower()
  
# now you can use the takecommand function where you want to recognize speech
# And please experiment with the above code 
# like what pause_threshold and energy_threshold do 
///////////---  *HAPPYCODING*  ---///////////

python code voice to text

# importing libraries 
import speech_recognition as sr 
import os 
from pydub import AudioSegment
from pydub.silence import split_on_silence

# create a speech recognition object
r = sr.Recognizer()

# a function that splits the audio file into chunks
# and applies speech recognition
def get_large_audio_transcription(path):
    """
    Splitting the large audio file into chunks
    and apply speech recognition on each of these chunks
    """
    # open the audio file using pydub
    sound = AudioSegment.from_wav(path)  
    # split audio sound where silence is 700 miliseconds or more and get chunks
    chunks = split_on_silence(sound,
        # experiment with this value for your target audio file
        min_silence_len = 500,
        # adjust this per requirement
        silence_thresh = sound.dBFS-14,
        # keep the silence for 1 second, adjustable as well
        keep_silence=500,
    )
    folder_name = "audio-chunks"
    # create a directory to store the audio chunks
    if not os.path.isdir(folder_name):
        os.mkdir(folder_name)
    whole_text = ""
    # process each chunk 
    for i, audio_chunk in enumerate(chunks, start=1):
        # export audio chunk and save it in
        # the `folder_name` directory.
        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
        audio_chunk.export(chunk_filename, format="wav")
        # recognize the chunk
        with sr.AudioFile(chunk_filename) as source:
            audio_listened = r.record(source)
            # try converting it to text
            try:
                text = r.recognize_google(audio_listened)
            except sr.UnknownValueError as e:
                print("Error:", str(e))
            else:
                text = f"{text.capitalize()}. "
                print(chunk_filename, ":", text)
                whole_text += text
    # return the text for all chunks detected
    return whole_text

how to fix speech recognition in python

import speech_recognition as sr
r = sr.Recognizer()
with sr.Microphone() as source:                # use the default microphone as the audio source
    audio = r.listen(source)                   # listen for the first phrase and extract it into audio data

try:
    print("You said " + r.recognize(audio))    # recognize speech using Google Speech Recognition
except LookupError:                           # speech is unintelligible
    print("Could not understand audio")