User:Angeliki/2nd Trimester: Difference between revisions

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== OCR ==
== OCR ==
=== Tesseract training: ===
=== Tesseract training ===
[[Install Tesseract 4.0-Ubuntu|1. Install Tesseract]]<br />
[[Install Tesseract 4.0-Ubuntu|1. Install Tesseract]]<br />
2. Recipe for training
2. Recipe for training


== Reading- Writing ==
== Reading- Writing ==
[[Synopsis_24-1-2018#Reading-_Angeliki|Synopsis]]
[[Synopsis_24-1-2018#Reading-_Angeliki|Synopsis]]<br />
[[Essay21Feb|Comparative essay]]


== Reader ==
== Reader ==
[https://pzwiki.wdka.nl/mw-mediadesign/images/7/71/XPUB_reader_concept.pdf Mini reader]
[https://pzwiki.wdka.nl/mw-mediadesign/images/7/71/XPUB_reader_concept.pdf Mini reader]


== Python scripts ==
[[Reader#6/Angeliki|Reader#6<br />
=== '''"Python whisperer"''' ===
 
<syntaxhighlight lang="python" line='line'>
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))
</syntaxhighlight>
{|
|-
|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?<br />


''From a [http://pracownia.audiosfery.uni.wroc.pl/wp-content/uploads/2016/12/Audiosfera-2_2015_Hildegard-WesterkampEN.pdf text] of Hildegard Westerkamp''
<big>''~~ From Tedious Tasks to Liberating Orality ~~''</big>]]


Cover made with Graphviz


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== [[Angeliki/PROTOTYPING 2|Python scripts]] ==


''The output text with borrowed nouns from [[Synopsis_24-1-2018|synopsis of several texts]]''
== The secrets of pocketsphinx ==
|}
=== Acoustic model/training ===
what

Latest revision as of 18:52, 24 March 2018


OCR

Tesseract training

1. Install Tesseract
2. Recipe for training

Reading- Writing

Synopsis
Comparative essay

Reader

Mini reader

Reader#6
~~ From Tedious Tasks to Liberating Orality ~~

Cover made with Graphviz

Python scripts

The secrets of pocketsphinx

Acoustic model/training

what