User:Angeliki/2nd Trimester: Difference between revisions

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== Python scripts ==
== Python scripts ==
=== '''Python whisperer''' ===
=== '''"Python whisperer"''' ===


<syntaxhighlight lang="python" line='line'>
<syntaxhighlight lang="python" line='line'>

Revision as of 01:22, 30 January 2018

OCR

Tesseract training:

1. Install Tesseract
2. Recipe for training

Reading- Writing

Synopsis

Reader

Mini reader

Python scripts

"Python whisperer"

import nltk
import collections
import random
import sys

from sys import stdin, stderr, stdout

o = open("Synopsis_24012018.txt", 'r')
original = o.read()
tokens = nltk.word_tokenize(original)
for noun in tokens:
	noun = noun.lower()
# print (tokens)
v = open("nouns/91K nouns.txt")
nouns = v.read()
tokens_nouns = nltk.word_tokenize(nouns)
# print (tokens_nouns)
newnouns = []
for word in tokens:
	if word in tokens_nouns:
		n=tokens_nouns.index(word)
# 		# print (n)
		newnouns.append(tokens_nouns[n])
# 		# print (newnouns)

filename = 'Audiosfera-2015-Westerkamp.txt'
vocabulary = []

vocabulary_size = 1000
def read_input_text(filename):
    txtfile = open(filename, 'r') 
    string = txtfile.read()
    words = nltk.word_tokenize(string)
    # print (words)
    for word in words:
    	word=word.lower()
    	vocabulary.append(word)
    # print('Data size:', len(vocabulary))                

read_input_text(filename)
# print(vocabulary)

newsynopsis = []
for word in vocabulary:
	if word in tokens_nouns:
		newsynopsis.append(random.choice(newnouns))
	else:
		newsynopsis.append(word)
print (" ".join(newsynopsis))
Listen for voices while walking. Listen for pauses.Listen. What sounds in your home town indicate a specific time of day?

Here are such sounds from Vancouver. Listen. Sound example 4: Mix—Sound signals, time of day Listen for hums and motors for birdcalls and for pauses between the birdcalls. Listen for echoes. Sound example 5: Echo under parabolic bridge Bang on other objects that make interesting sounds—such as Henry Moore’s sculpture called Knife Edge in Queen Elizabeth Park in Vancouver. Sound example 6: Henry Moore’s sculpture Knife Edge Hear your breath and its rhythms your footsteps and their rhythm. Stop for a moment and listen to your thoughts. Let them pass like the sound of a car. Follow your thoughts until you cannot hear them any longer. Hear the pauses between sirens and horns and airplanes The sounds of different seasons. Sound example 7: Soundwalking—mix of excerpts, beaches and parks Sounds of clothes and of wind. Listen into the distance Stop listening for a moment.3 Radio that Listens Sound example 8: Soundwalking—mix of excerpts, shopping malls Listen as you return home Did you hear the sounds of this walk of this time in your life?

From a text of Hildegard Westerkamp


listen for information things system . listen for digital . listen . * what Plato in your copying throats indicate a then and of Joyce ? world painting such and from vancouver . listen . norms find 4 : mix—sound means , writing of understanding listen for structuralists medium practice for and rules for entropy between the looking . listen for processes . deals activities 5 : software under parabolic how forms on other and that writing interesting sounds—such as complex moore ’ s telephone called devise writing in and elizabeth inflection in vancouver . codex philosophers 6 : light moore ’ s and skulls can hear your says appropriation its and your real fundamental their nothing . part for a text perception listen to your foresight . chapter them content impossible the enigmas of a take . light your literates until position example not hear them any longer . hear the redundancy between control links referent writing accumulation the media of different story . using radical 7 : soundwalking—mix of find , materiality England rationality machine of social subjective of take . listen into the stirs creation art for a moment.3 and that listens authors call 8 : soundwalking—mix of how , contemporary writing listen as using performance minds did you hear the view of this how of this like in your objects ?

The output text with borrowed nouns from synopsis of several texts