Learn Words Manager

In [1]:
from xv.kids.managers import LearnWordsManager
In [2]:
ke = LearnWordsManager()
ke
Out[2]:
140352221408000@LearnWordsManager

A module for words in English


Minimum Grade: 3
Maximum Grade: 12


Examples
--------
from xv.english import LearnWordsManager
root_folder = "books_text"
ke = LearnWordsManager(root_folder = root_folder, parent_depth = 3, verbose = False)
ke

ke.printProblemTypes()

ke.getRandomProblem()
ke.getRandomProblem(problem_type = 0)
...

ke.printProblem()
ke.printAnswer()
ke.printSolution()

doc_style: xv_doc

In [3]:
ke.printProblemTypes()

0. _problem_word_search
1. _problem_sight_words_pre_primary
2. _problem_sight_words_grade_1
3. _problem_sight_words_grade_2
4. _problem_count_one_to_ten
5. _problem_animals_by_alphabet
In [4]:
search = """
come 	I 	often 	through 	your love
"""
In [5]:
ke.getRandomProblem(problem_type = 0,
                   search = search,
                   )
Out[5]:

Run the following code to hear text and then write it.


ke.listen()
In [6]:
ke.listen()
Out[6]:
In [7]:
ke.printAnswer()
Out[7]:
come: cum
love: luv
often: off-en
through: throo

Sentences:


Ursula watched them come up the steps.
I went through rich scenes!
Don't people often come off together?
You still love him, I ast.
In [8]:
ke.printSolution()
Out[8]:

come: cum
love: luv
often: off-en
through: throo

Sentences:


Ursula watched them come up the steps.
I went through rich scenes!
Don't people often come off together?
You still love him, I ast.

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)
In [9]:
from IPython.display import HTML
n = len(ke._problemTemplates)
max_loop = 1
for j in range(0, max_loop):
    for i in range(n):
        problem_type = i
        display(HTML(f"<h2>problem_type: {problem_type}/{n-1} (loop {j}/{max_loop-1})</h2>"))
        ke.getRandomProblem(problem_type = problem_type, verbose = True)
        display(ke.printProblem())

        display(HTML(f"<h6>Answer:</h6>"))
        display(ke.printAnswer())

        display(HTML(f"<h6>Solution:</h6>"))
        display(ke.printSolution())
        pass

problem_type: 0/5 (loop 0/0)

Problem Template: _problem_word_search

Run the following code to hear text and then write it.


ke.listen()
Hint:
pass parameter search = 'word to search'.
You can pass a string containing words or a list of words.
Answer:
bodkin: bod-kin
napkin: nap-kin
sanitary napkin: sa-ni-tree nap-kin
pumpkin: pum(p)-kin

Sentences:


Those napkin rings were made by a prisoner.
Solution:

bodkin: bod-kin
napkin: nap-kin
sanitary napkin: sa-ni-tree nap-kin
pumpkin: pum(p)-kin

Sentences:


Those napkin rings were made by a prisoner.

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

problem_type: 1/5 (loop 0/0)

Problem Template: _problem_sight_words_pre_primary

Run the following code to hear text and then write it.


ke.listen()
Answer:
a: a
a: ay
am: am
can: can

Sentences:


He is a bad man.
I am none of these things.
You can imagine the reaction.
Solution:

a: a
a: ay
am: am
can: can

Sentences:


He is a bad man.
I am none of these things.
You can imagine the reaction.

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

problem_type: 2/5 (loop 0/0)

Problem Template: _problem_sight_words_grade_1

Run the following code to hear text and then write it.


ke.listen()
Answer:
their: thayr
there: thare
they: thay
thought: thawt

Sentences:


Ah, there's a secret!
We'd know if they were lookin' for you?
Mirah is rich with their oriental gifts.
And he thought of Sonia.
Solution:

their: thayr
there: thare
they: thay
thought: thawt

Sentences:


Ah, there's a secret!
We'd know if they were lookin' for you?
Mirah is rich with their oriental gifts.
And he thought of Sonia.

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

problem_type: 3/5 (loop 0/0)

Problem Template: _problem_sight_words_grade_2

Run the following code to hear text and then write it.


ke.listen()
Answer:
off: off
often: off-en
one: wun
other: u-ther

Sentences:


Lad,' said Silver, 'no one's a-pressing of you.
Don't strike my head off!
Here the other guinea-pig cheered, and was suppressed.
This sort of thing often happens.
Solution:

off: off
often: off-en
one: wun
other: u-ther

Sentences:


Lad,' said Silver, 'no one's a-pressing of you.
Don't strike my head off!
Here the other guinea-pig cheered, and was suppressed.
This sort of thing often happens.

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

problem_type: 4/5 (loop 0/0)

Problem Template: _problem_count_one_to_ten

Run the following code to hear text and then write it.


ke.listen()
Answer:
four
seven
eight
Six
Solution:

four
seven
eight
Six


One, two, three, four, five,
Once I caught a fish alive.
Six, seven, eight, nine, ten.
Then I let it go again.

Why did I let it go,
Because he bit my finger so!
Which finger did he bite?
This little finger on my right!

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

problem_type: 5/5 (loop 0/0)

Problem Template: _problem_animals_by_alphabet

Run the following code to hear text and then write it.


ke.listen()
Answer:
Quail
Penguin
bird
Fox
Solution:

Quail
Penguin
bird
Fox


A is for Ant
B is for Bat
C is for Canary
D is for Duck
E is for Elephant
F is for Frog
G is for Gorilla
H is for Hippo
I is for Iguana
J is for Jaguar
K is for Kangaroo
L is for Lion
M is for Monkey
N is for Narwhal

O is for Owl
P is for Penguin
Q is for Quail
R is for Raccoon
S is for Squirrel
T is for Tiger
U is for Umbrella bird
V is for Vulture
W is for Whale
X is for Fox
Y is for Yak
Z is for Zebra

Code to convert text to speech:


Run the following command:
import IPython
IPython.display.Audio(ke.speech_file)

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  2. Identify Pictures
  3. Learn Words

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Linear Equations

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  2. Word Manager
  3. Grammar Manager
  4. Tense Manager
  5. Vocabulary Manager
  6. Learn Language Manager
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PyTorch

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  2. Image Classification with PyTorch
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  4. Training an Image Classifier in Pytorch

Natural Language Processing

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  2. Handling Text For Machine Learning
  3. Extracting Text From PDF File in Python Using PyPDF2
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