def main():
"""Shows basic usage of the Google Calendar API.
Creates a Google Calendar API service object and outputs a list of the next
10 events on the user's calendar.
"""
credentials = get_credentials()
http = credentials.authorize(httplib2.Http())
service = discovery.build('calendar', 'v3', http=http)
now = datetime.datetime.utcnow().isoformat(
) + 'Z' # 'Z' indicates UTC time
print('Getting the upcoming 10 events')
eventsResult = service.events().list(calendarId='primary',
timeMin=now,
maxResults=10,
singleEvents=True,
orderBy='startTime').execute()
events = eventsResult.get('items', [])
if not events:
print('No upcoming events found.')
for event in events:
start = event['start'].get('dateTime', event['start'].get('date'))
print(start, event['summary'])
es = espeak.ESpeak()
es.say(start)
es.say(event['summary'])
def __init__(self, view):
# Engine to produce sound for any word
# self.es = espeak.ESpeak()
self.NUMBER_OF_LEVELS = 2
self.view = view
self.view.window.connect("key-press-event", self.readKey)
self.view.vbox.connect('expose-event', self.addImage)
# Functions for the buttons
self.left_button_signal = self.view.left_button.connect(
"clicked", self.play_word)
self.right_button_signal = self.view.right_button.connect(
"clicked", self.next_word, "Next Word")
# Fields of the controller
self.level = 0
self.score = 0
self.dictionary = {} # A dictionary of all the words used in the game
self.level_words = [] # the list of words to be played
self.currentIndex = 0 # index of the current word that is pronounced
self.check_current_word = False # keep track of whether the current word has been checked
self.typed = "" # keeps track of what the user has typed so far
self.skipped = [] # list of words that are skipped
self.misspelled = {
} # dictionary of misspelled words and the number of times the user misspelled each word
# Set the game up for the first level
self.next_level()
self.view.typeBox.createTextBoxes(len(self.level_words[0]))
self.es = espeak.ESpeak(voice="en+f1", speed=200)
def doTTS(self, textContent):
es = espeak.ESpeak()
es.voice = 'en+f4'
es.speed = 100
es.capitals = 25
file_name = "{}_{}.wav".format(textContent, format(time.time(), ".0f"))
full_file_path = "{}{}".format(sounds_path, file_name)
es.save(textContent, full_file_path)
print("save file name:{}".format(full_file_path))
return file_name
def setUp(self):
self.e = espeak.ESpeak()
def test_init_arg(self):
self.e = espeak.ESpeak(amplitude=10)
self.assertEqual(self.e.args['amplitude'][1], 10)
import networkx as nx
import collections
import json
import io
import os
import sys
import matplotlib.pyplot as plt
import argparse, random
from pycorenlp import StanfordCoreNLP
from Globals import Globals
from networkx.classes.function import neighbors
import espeak
#https://github.com/relsi/python-espeak
male = espeak.ESpeak(amplitude=200, word_gap=-50, pitch=36, speed=200, voice='english-us')
female = espeak.ESpeak(amplitude=200, word_gap=-50, pitch=77, speed=200, voice='english-us')
#male.say("John moved to the office")
#female.say("Sandra journeyed to the bathroom")
#female.say("Mary moved to the hallway")
#male.say("Daniel travelled to the office")
#female.say("John went back to the garden")
#male.say("John moved to the bedroom")
class babiGraph():
def __init__(self):
self.edgeList=[]
self.nodeList=[]
self.timeStampLemmaDict = dict()
self.subStoryFacts = dict()
self.G=nx.Graph()
import time
import espeak
import paho.mqtt.client as mqtt
broker_address = "192.168.1.32"
import RPi.GPIO as GPIO
es = espeak.ESpeak()
test_msg = "Speaker is connected"
es.say(test_msg)
# setup button
GPIO.setmode(GPIO.BCM)
GPIO.setup(23, GPIO.IN, pull_up_down=GPIO.PUD_DOWN)
if GPIO.input(23) == 0:
print("button pressed")
#define callback
def on_message(client, userdata, message):
time.sleep(1)
print("received message =", str(message.payload.decode("utf-8")))
text_message = str(message.payload.decode("utf-8"))
es.say(text_message)
def on_disconnect(client, userdata, rc):
error_message = str(rc)
es.say("disconnected because " + error_message)
def rap(tweet):
rap = build_rap(tweet)
es = espeak.ESpeak(pitch=1)
es.say(rap)
def speak():
es = espeak.ESpeak()
# es.say(pas)
filename = datetime.now().strftime('%Y%m%d_%H:%M:%S')
wav = filename +".wav"
es.save(pas, wav)
import io
import os
import sys
import matplotlib.pyplot as plt
import argparse, random
from pycorenlp import StanfordCoreNLP
from Globals import Globals
from networkx.classes.function import neighbors
from babiparser import BabiParser
import time
# TODO: make this optional
import espeak
#https://github.com/relsi/python-espeak
female = espeak.ESpeak(amplitude=200,
word_gap=-50,
pitch=36,
speed=220,
voice='en-us')
male = espeak.ESpeak(amplitude=200,
word_gap=-50,
pitch=80,
speed=220,
voice='en-us+f4')
class ActionClassifier(object):
def __init__(self, input_action, model=None):
# Label -> set of Actions
with open(input_action, 'r') as annotatedActions:
actions = json.load(annotatedActions)
actionsDict = {}
def __init__(self):
rospy.init_node(self.NODE_NAME)
self.sub = rospy.Subscriber('/tts_text', String, self.tts_callback)
self.es = espeak.ESpeak()
def __init__(self, word):
super(Speak, self).__init__()
self._stop = threading.Event()
self.word = word
self.es = espeak.ESpeak(voice="en+f1", speed=230)