diff --git a/BitLit_decoder.py b/BitLit_decoder.py index ae1d60e..3aa0776 100644 --- a/BitLit_decoder.py +++ b/BitLit_decoder.py @@ -1,32 +1,21 @@ -#### RUNNING THE MODEL -#Michels-MacBook-Pro:~ ShebMichel$ cd documents/pmlg/wake/decoder -#Michels-MacBook-Pro:decoder ShebMichel$ python demo.py resources/HiBitLit.pmdl -import sys, os +#### RUNNING THE MODEL +# Michels-MacBook-Pro:~ ShebMichel$ cd documents/pmlg/wake/decoder +# Michels-MacBook-Pro:decoder ShebMichel$ python demo.py resources/HiBitLit.pmdl +import os import sys import snowboydecoder import signal -#import BitLit_main ## MAIN PROGRAM -#### -from gtts import gTTS ## Packages for Text to voice -import speech_recognition as sr ## Packages for voice recognizer -import BitLit_main -# import tensorflow as tf -# tf.enable_eager_execution() -# from tensorflow.keras.layers import Embedding, GRU, Dense import numpy as np -import re -from textblob import TextBlob -import random -import poem_generator ## POEM GENERATOR IMPORT -from poem_generator import* import time +import BitLit_main -t0=time.time() ## Time counter +t0 = time.time() ## Time counter interrupted = False + def signal_handler(signal, frame): global interrupted interrupted = True @@ -36,6 +25,7 @@ def interrupt_callback(): global interrupted return interrupted + if len(sys.argv) == 1: print("Error: need to specify model name") print("Usage: python demo.py your.model") @@ -47,14 +37,16 @@ model = sys.argv[1] signal.signal(signal.SIGINT, signal_handler) detector = snowboydecoder.HotwordDetector(model, sensitivity=0.5) -print('Listening... Press Ctrl+C to exit') +print("Listening... Press Ctrl+C to exit") -detector.start(detected_callback=BitLit_main.generate_poem, - interrupt_check=interrupt_callback, - sleep_time=0.03) +detector.start( + detected_callback=BitLit_main.generate_poem, + interrupt_check=interrupt_callback, + sleep_time=0.03, +) detector.terminate() -t1 =time.time() -total=t1-t0 -print(('Time spent is about:', np.round(total), 'seconds')) +t1 = time.time() +total = t1 - t0 +print(("Time spent is about:", np.round(total), "seconds"))