mirror of
https://github.com/wassname/BitLit_test1.git
synced 2026-06-27 19:28:58 +08:00
wassname
141 lines
4.0 KiB
Python
141 lines
4.0 KiB
Python
"""
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Voice to text to poem to speech
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Credits: Michel, Lauren, Thomas
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"""
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# https://pythonprogramminglanguage.com/text-to-speech/
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## cmd 1:::: sudo pip install gTTS
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## cmd 2:::: sudo pip install pyttsx
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import sys
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from gtts import gTTS ## Packages for Text to voice
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import os
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import numpy as np
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import re
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from textblob import TextBlob
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import random
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import pyglet
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import json
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import time
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import datetime
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import hashlib
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import tempfile
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from logger import logger
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from snowboydecoder import play_audio_file
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import speech_recognition as sr ## Packages for voice recognizer
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for index, name in enumerate(sr.Microphone.list_microphone_names()):
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logger.debug("Microphone with name \"{1}\" found for `Microphone(device_index={0})`".format(index, name))
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from poem_generator import poem
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# Load credentials
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try:
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GOOGLE_CLOUD_SPEECH_CREDENTIALS = open("secrets/google_cloud_credentials.json").read()
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except:
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print('you should place google cloud json credentials at "secrets/google_cloud_credentials.json", make sure you enable the speech recognition api')
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GOOGLE_CLOUD_SPEECH_CREDENTIALS = None
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def play_mp3(mp3_file):
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"""Play mp3 file with pyglet."""
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source = pyglet.media.load(filename=mp3_file, streaming=False)
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source.play()
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time.sleep(source.duration + 2) # must be a better way to wait untill the media has played
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def cache_gtts(text, lang="en-au", cache_file=None):
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"""
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Cache calls to gtts.
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Saves each to a temporary file
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languages
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en-au: English (Australia)
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en-ca: English (Canada)
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en-gb: English (UK)
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en-gh: English (Ghana)
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en-ie: English (Ireland)
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en-in: English (India)
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en-ng: English (Nigeria)
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en-nz: English (New Zealand)
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en-ph: English (Philippines)
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en-tz: English (Tanzania)
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en-uk: English (UK)
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en-us: English (US)
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en-za: English (South Africa)
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en: English
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"""
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if not cache_file:
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hash_filename = hashlib.md5(text.encode()).hexdigest() + '.mp3'
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cache_file = os.path.join(tempfile.gettempdir(), hash_filename)
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if not os.path.isfile(cache_file):
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tts = gTTS(text=text, lang=lang)
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tts.save(cache_file)
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return cache_file
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def generate_poem():
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############ AUDIO CONVERSION TO TEST
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play_audio_file()
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t0 = time.time()
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r = sr.Recognizer()
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with sr.Microphone() as source:
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outfile1 = cache_gtts(text="Hi! My Name is BIT-LIT. PLEASE SPEAK. You have 20 seconds before the beep.")
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play_mp3(outfile1)
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print("SPEAK NOW-SPEAK:", source)
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audio = r.listen(source, phrase_time_limit=20)
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# speech_recognition.WaitTimeoutError
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print('Recorded audio', audio)
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outfile2 = cache_gtts(text="BEEP. THANK YOU! GIVE ME A SECOND TO READ OUT YOUR POEM")
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play_mp3(outfile2)
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t1 = time.time()
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print('listen took', t1 - t0)
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try:
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print("using google speech to text...")
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USER_INPUT = r.recognize_google_cloud(audio, credentials_json=GOOGLE_CLOUD_SPEECH_CREDENTIALS)
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print("Google thinks you said: " + USER_INPUT)
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except sr.UnknownValueError as e:
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print("Could not understand audio. {}".format(e))
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except sr.RequestError as e:
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print("Could not request results; {0}".format(e))
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t1b = time.time()
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print('transcribe took', t1b - t1)
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# Generate poem from user seed
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text_generated = poem(USER_INPUT)
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t2 = time.time()
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print("ML POEM is:", text_generated, 'in', t2 - t1)
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# TEXT CONVERSION IN AUDIO
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# FEED POEM TO TRANSCRIBER
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tts = gTTS(text=text_generated, lang="en")
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ts = datetime.datetime.utcnow().strftime('%Y%m%d_%H-%M-%S')
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poem_mp3 = "outputs/BitLit_{}.mp3".format(ts)
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tts.save(poem_mp3)
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play_mp3(poem_mp3)
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print("BIT-LIT ENDING STATEMENT:")
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outfile = cache_gtts(text="THANK YOU! BEEP.", lang="en")
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play_mp3(outfile)
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######
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t3 = time.time()
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print('Poem to speech took', t3 - t2)
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print("Time spent is about:", np.round(t3 - t0), "seconds")
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if __name__ == "__main__":
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generate_poem()
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