voice_recognition.py

import sys
import queue
import argparse
import sounddevice as sd
import json
from vosk import Model, KaldiRecognizer, SetLogLevel

SetLogLevel(-1)

q = queue.Queue()
def int_or_str(text):
    """Helper function for argument parsing."""
    try:
        return int(text)
    except ValueError:
        return text


def callback(indata, frames, time, status):
    """This is called (from a separate thread) for each audio block."""
    if status:
        print(status, file=sys.stderr)
    q.put(bytes(indata))


parser = argparse.ArgumentParser(add_help=False)
parser.add_argument(
    "-l", "--list-devices", action="store_true",
    help="show list of audio devices and exit")
args, remaining = parser.parse_known_args()
if args.list_devices:
    parser.exit(0)
parser = argparse.ArgumentParser(
    description=__doc__,
    formatter_class=argparse.RawDescriptionHelpFormatter,
    parents=[parser])
parser.add_argument(
    "-f", "--filename", type=str, metavar="FILENAME",
    help="audio file to store recording to")
parser.add_argument(
    "-d", "--device", type=int_or_str,
    help="input device (numeric ID or substring)")
parser.add_argument(
    "-r", "--samplerate", type=int, help="sampling rate")
parser.add_argument(
    "-m", "--model", type=str, help="language model; e.g. en-us, fr, nl; default is en-us")
args = parser.parse_args(remaining)
try:
    if args.samplerate is None:
        device_info = sd.query_devices(args.device, "input")
        # soundfile expects an int, sounddevice provides a float:
        args.samplerate = int(device_info["default_samplerate"])

    if args.model is None:
        model = Model(lang="en-us")
    else:
        model = Model(lang=args.model)

    if args.filename:
        dump_fn = open(args.filename, "wb")
    else:
        dump_fn = None



except KeyboardInterrupt:
    print("\nDone")
    parser.exit(0)

def voice_input():
    model = Model(lang="en-us")
    print("You:")
    with sd.RawInputStream(samplerate=args.samplerate, blocksize=8000, device=args.device,
                           dtype="int16", channels=1, callback=callback):

        rec = KaldiRecognizer(model, args.samplerate)
        while True:
            data = q.get()
            if rec.AcceptWaveform(data):
                a = json.loads(rec.Result())
                a = str(a['text'])
                a = ' '.join(a.split())
                if(len(a) > 0):
                    print(a)
                    user_input = a
                    return user_input
            if dump_fn is not None:
                dump_fn.write(data)
            


                
if __name__ == "__main__":
    resp = voice_input()